General Keywords

[ Algorithms ] [ Algorithms; Optimization ] [ Applications ] [ Data, Challenges, Implementations, and Software ] [ Deep Learning ] [ Deep Learning; Deep Learning ] [ Neuroscience and Cognitive Science ] [ Optimization ] [ Optimization; Optimization ] [ Probabilistic Methods ] [ Probabilistic Methods; Probabilistic Methods ] [ Reinforcement Learning and Planning ] [ Social Aspects of Machine Learning ] [ Theory ] [ Theory; Theory ]

Topic Keywords

[ Active Learning ] [ Active Learning; Algorithms ] [ Activity and Event Recognition ] [ Adaptive Data Analysis; Optimization ] [ Adversarial Examples ] [ Adversarial Learning ] [ Adversarial Learning; Algorithms ] [ Adversarial Networks ] [ Adversarial Networks ] [ Adversarial Networks; Deep Learning ] [ Adversarial Networks; Deep Learning ] [ AI Safety ] [ Algorithms Evaluation ] [ Approximate Inference ] [ Architectures ] [ Attention Models ] [ Audio and Speech Processing ] [ AutoML ] [ Bandit Algorithms ] [ Bandit Algorithms; Algorithms ] [ Bandit Algorithms; Reinforcement Learning and Planning ] [ Bandit Algorithms; Reinforcement Learning and Planning ] [ Bandits ] [ Bayesian Deep Learning ] [ Bayesian Methods ] [ Bayesian Nonparametrics ] [ Bayesian Theory ] [ Bayesian Theory ] [ Benchmarks ] [ Biologically Plausible Deep Networks ] [ Biologically Plausible Deep Networks; Deep Learning ] [ Biologically Plausible Deep Networks; Neuroscience and Cognitive Science ] [ Body Pose, Face, and Gesture Analysis ] [ Body Pose, Face, and Gesture Analysis; Applications ] [ Boosting and Ensemble Methods ] [ Boosting and Ensemble Methods; Algorithms ] [ Boosting and Ensemble Methods; Probabilistic Methods; Probabilistic Methods ] [ Causal Inference ] [ Classification ] [ Classification; Algorithms ] [ Classification; Algorithms ] [ Classification; Applications ] [ Classification; Deep Learning; Deep Learning ] [ Classification; Deep Learning; Deep Learning ] [ Clustering ] [ Clustering; Applications ] [ Clustering; Theory ] [ CNN Architectures; Deep Learning ] [ CNN Architectures; Deep Learning ] [ CNN Architectures; Theory ] [ Cognitive Science; Neuroscience and Cognitive Science ] [ Collaborative Filtering ] [ Collaborative Filtering; Algorithms ] [ Collaborative Filtering; Applications ] [ Combinatorial Optimization ] [ Components Analysis (e.g., CCA, ICA, LDA, PCA) ] [ Computational Biology and Bioinformatics ] [ Computational Biology and Bioinformatics; Applications ] [ Computational Complexity ] [ Computational Learning Theory ] [ Computational Photography ] [ Computational Social Science ] [ Computer Vision ] [ Computer Vision; Applications ] [ Computer Vision; Applications ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Computer Vision; Deep Learning ] [ Continual Learning ] [ Convex Optimization ] [ Convex Optimization; Optimization ] [ Convex Optimization; Probabilistic Methods; Theory; Theory ] [ Convex Optimization; Theory ] [ Crowdsourcing ] [ Decision and Control ] [ Deep Autoencoders; Deep Learning ] [ Deep learning Theory ] [ Deep RL ] [ Density Estimation ] [ Density Estimation; Deep Learning ] [ Derivative Free Optimization ] [ Dialog- or Communication-Based Learning ] [ Dimensionality Reduction ] [ Distributed and Parallel Optimization ] [ Distributed Inference ] [ Efficient Inference Methods ] [ Efficient Training Methods; Deep Learning ] [ Embedding and Representation learning ] [ Embedding Approaches ] [ Exploration ] [ Fairness, Accountability, and Transparency ] [ Fairness, Accountability, and Transparency ] [ Few-Shot Learning ] [ Few-Shot Learning; Algorithms ] [ Frequentist Statistics ] [ Game Theory and Computational Economics ] [ Gaussian Processes ] [ Gaussian Processes and Bayesian non-parametrics ] [ Generative Models ] [ Generative Models ] [ Graphical Models ] [ Graphical Models ] [ Hardware and Systems ] [ Healthcare ] [ Human or Animal Learning ] [ Human or Animal Learning; Probabilistic Methods ] [ Image Segmentation ] [ Image Segmentation; Algorithms ] [ Image Segmentation; Applications ] [ Information Theory ] [ Kernel Methods ] [ Kernel Methods; Optimization ] [ Large Deviations and Asymptotic Analysis ] [ Large Scale Learning ] [ Large Scale Learning; Algorithms ] [ Large Scale Learning; Algorithms ] [ Large Scale Learning; Applications ] [ Large Scale Learning; Deep Learning ] [ Large Scale Learning; Probabilistic Methods ] [ Latent Variable Models ] [ Learning Theory ] [ Markov Decision Processes ] [ Markov Decision Processes; Reinforcement Learning and Planning ] [ Markov Decision Processes; Reinforcement Learning and Planning ] [ Matrix and Tensor Factorization ] [ MCMC ] [ Memory ] [ Memory; Optimization ] [ Meta-Learning ] [ Meta-Learning; Applications ] [ Metric Learning ] [ Missing Data; Algorithms ] [ Missing Data; Algorithms ] [ Missing Data; Theory ] [ Model Selection and Structure Learning ] [ Models of Learning and Generalization ] [ Monte Carlo Methods ] [ Multi-Agent RL ] [ Multimodal Learning ] [ Multitask and Transfer Learning ] [ Multitask and Transfer Learning; Algorithms ] [ Multitask and Transfer Learning; Probabilistic Methods ] [ Multitask, Transfer, and Meta Learning ] [ Natural Language Processing ] [ Network Analysis ] [ Networks and Relational Learning ] [ Neural Coding; Neuroscience and Cognitive Science ] [ Neuroscience ] [ Neuroscience and Cognitive Science ] [ Non-Convex Optimization ] [ Non-Convex Optimization ] [ Non-Convex Optimization; Theory ] [ Non-parametric models ] [ Object Detection; Deep Learning ] [ Object Detection; Neuroscience and Cognitive Science ] [ Online Learning ] [ Online Learning Algorithms ] [ Online Learning Theory ] [ Online Learning; Theory ] [ Optimal Transport ] [ Optimization for Deep Networks ] [ Others ] [ Others ] [ Others ] [ Others ] [ Others ] [ Planning and Control ] [ Plasticity and Adaptation ] [ Predictive Models ] [ Predictive Models; Deep Learning ] [ Predictive Models; Deep Learning ] [ Privacy, Anonymity, and Security ] [ Privacy, Anonymity, and Security ] [ Probabilistic Methods ] [ Probabilistic Programming ] [ Program Understanding and Generation ] [ Quantitative Finance and Econometrics ] [ Ranking and Preference Learning ] [ Ranking and Preference Learning; Theory ] [ Reasoning; Optimization ] [ Recommender Systems ] [ Recurrent Networks ] [ Recurrent Networks; Theory ] [ Regression ] [ Regression; Algorithms ] [ Regression; Applications ] [ Regression; Optimization ] [ Regression; Probabilistic Methods; Probabilistic Methods ] [ Regularization ] [ Regularization ] [ Reinforcement Learning ] [ Reinforcement Learning and Planning ] [ Relational Learning ] [ Representation Learning ] [ Representation Learning; Algorithms ] [ Representation Learning; Algorithms ] [ Representation Learning; Neuroscience and Cognitive Science ] [ Representation Learning; Neuroscience and Cognitive Science; Neuroscience and Cognitive Science ] [ Representation Learning; Optimization ] [ RL, Decisions and Control Theory ] [ Robotics ] [ Robust statistics ] [ Semi-Supervised Learning ] [ Social Aspects of Machine Learning ] [ Software Toolkits ] [ Spaces of Functions and Kernels ] [ Sparse Coding and Dimensionality Expansion; Applications ] [ Sparsity and Compressed Sensing ] [ Sparsity and Compressed Sensing; Applications ] [ Sparsity and Compressed Sensing; Optimization; Theory ] [ Speech Recognition ] [ Statistical Learning Theory ] [ Statistical Physics of Learning ] [ Stochastic Optimization ] [ Structured Prediction ] [ Submodular Optimization ] [ Supervised Learning ] [ Sustainability and Environment ] [ Theory ] [ Time Series Analysis ] [ Time Series Analysis; Deep Learning ] [ Time Series Analysis; Probabilistic Methods; Probabilistic Methods ] [ Time Series and Sequences ] [ Topic Models ] [ Uncertainty Estimation ] [ Uncertainty Estimation; Applications; Probabilistic Methods ] [ Unsupervised Learning ] [ Unsupervised Learning; Applications ] [ Unsupervised Learning; Deep Learning ] [ Variational Inference ] [ Visualization or Exposition Techniques for Deep Networks ] [ Visual Question Answering ] [ Visual Scene Analysis and Interpretation ]

783 Results

Expo Workshop
Sun 17:00 PaddlePaddle-based Deep Learning at Baidu
Dejing Dou, Chenxia Li, Teng Xi, Dingfu Zhou, Tianyi Wu, Xuhong Li, Zhengjie Huang, Guocheng Niu, Ji Liu, Yaqing Wang, Xin Wang, Qianwei Cai
Expo Talk Panel
Sun 17:13 Model fusion via single-round FL
Mikhail Yurochkin
Expo Workshop
Sun 18:30 Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond
Xuhong Li
Expo Workshop
Sun 20:20 Paddle Quantum: Towards Quantum Artificial Intelligence
Xin Wang
Tutorial
Mon 8:00 From ML research to ML products: A path towards building models with real-world impact
Reza Salimi-Khorshidi, Peyman Faratin
Tutorial
Mon 8:00 Part 1: Introduction to Sparsity in Deep Learning
Torsten Hoefler
Tutorial
Mon 8:00 Sparsity in Deep Learning: Pruning and growth for efficient inference and training
Torsten Hoefler, Dan Alistarh
Affinity Workshop
Mon 9:20 Deep Neural Network Uncertainty Estimation with Stochastic Inputs for Robust Aerial Navigation Policies
Fabio Arnez Yagualca, Huascar Espinoza, François Terrier
Affinity Workshop
Mon 10:25 Spotlights 2
Affinity Workshop
Mon 10:30 Ceramic Cracks Segmentation with Deep Learning
Gerivan Junior, Janderson Ferreira, Cristian Millán, Ramiro Ruiz, Alberto Junior, Bruno Fernandes
Tutorial
Mon 12:00 Random Matrix Theory and ML (RMT+ML)
Fabian Pedregosa, Courtney Paquette, Thomas Trogdon, Jeffrey Pennington
Affinity Workshop
Mon 13:45 Mask-net: Detection of Correct Use of Masks Through Computer Vision
Alexander Kalen, Alberto Landi, Nicolas Araque, Alejandro Marcano
Tutorial
Mon 14:15 The Mystery of Generalization: Why Does Deep Learning Work?
Jeffrey Pennington
Affinity Workshop
Mon 15:15 A Tree-Adaptation Mechanism for Covariate and Concept Drift
Leno Silva, Renato Vicente
Affinity Workshop
Mon 15:20 GAN-based Data Mapping for Model Adaptation
Leno Silva, Ruben Glatt, Renato Vicente
Tutorial
Mon 20:00 Privacy in learning: Basics and the interplay
Huishuai Zhang, Wei Chen
Oral Session
Tue 5:00 Deep Learning Applications
Oral Session
Tue 5:00 Deep Learning Architectures
Oral
Tue 5:00 Relative Positional Encoding for Transformers with Linear Complexity
Antoine Liutkus, Ondřej Cífka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gaël RICHARD
Oral
Tue 5:00 Attention is not all you need: pure attention loses rank doubly exponentially with depth
Yihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas
Spotlight
Tue 5:20 A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration
Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu
Spotlight
Tue 5:20 AutoSampling: Search for Effective Data Sampling Schedules
MING SUN, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui
Spotlight
Tue 5:25 HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik
Spotlight
Tue 5:25 A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang
Spotlight
Tue 5:30 Generative Adversarial Transformers
Drew A. Hudson, Larry Zitnick
Spotlight
Tue 5:30 Sliced Iterative Normalizing Flows
Biwei Dai, Uros Seljak
Spotlight
Tue 5:35 Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, JING YU, Ce Zhang, Gao Huang, Yunhai Tong
Spotlight
Tue 5:35 Preferential Temporal Difference Learning
Nishanth Anand, Doina Precup
Spotlight
Tue 5:40 Interpretable Stability Bounds for Spectral Graph Filters
Henry Kenlay, Dorina Thanou, Xiaowen Dong
Spotlight
Tue 5:40 Zoo-Tuning: Adaptive Transfer from A Zoo of Models
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long
Spotlight
Tue 5:45 SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
Wuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng
Spotlight
Tue 5:45 UnICORNN: A recurrent model for learning very long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Oral
Tue 6:00 Let's Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework
Floris Geerts, Filip Mazowiecki, Guillermo Perez
Oral
Tue 6:00 Neural Architecture Search without Training
Joe Mellor, Jack Turner, Amos Storkey, Elliot Crowley
Oral
Tue 6:00 Leveraging Sparse Linear Layers for Debuggable Deep Networks
Eric Wong, Shibani Santurkar, Aleksander Madry
Oral
Tue 6:00 Principled Simplicial Neural Networks for Trajectory Prediction
Mitch Roddenberry, Nicholas Glaze, Santiago Segarra
Oral
Tue 6:00 Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Will Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris Maddison
Oral Session
Tue 6:00 Deep Learning Algorithms 1
Oral Session
Tue 6:00 Deep Learning (Bayesian)
Oral
Tue 6:00 PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtarik
Oral Session
Tue 6:00 Deep Learning Algorithms 2
Oral Session
Tue 6:00 Deep Learning Theory 1
Oral
Tue 6:00 What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov, Sharad Vikram, Matt Hoffman, Andrew Wilson
Spotlight
Tue 6:20 Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
Spotlight
Tue 6:20 Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
Alex Immer, Matthias Bauer, Vincent Fortuin, Gunnar Ratsch, Khan Emtiyaz
Spotlight
Tue 6:20 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Spotlight
Tue 6:20 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
Spotlight
Tue 6:25 Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson
Spotlight
Tue 6:25 Self-Tuning for Data-Efficient Deep Learning
Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang
Spotlight
Tue 6:25 GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji
Spotlight
Tue 6:25 Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation
Aurick Zhou, Sergey Levine
Spotlight
Tue 6:25 A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
Spotlight
Tue 6:25 On Monotonic Linear Interpolation of Neural Network Parameters
James Lucas, Juhan Bae, Michael Zhang, Stanislav Fort, Richard Zemel, Roger Grosse
Spotlight
Tue 6:30 Connecting Sphere Manifolds Hierarchically for Regularization
Damien Scieur, Youngsung Kim
Spotlight
Tue 6:30 Deep kernel processes
Laurence Aitchison, Adam Yang, Sebastian Ober
Spotlight
Tue 6:30 KNAS: Green Neural Architecture Search
Jingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu SUN, Hongxia Yang
Spotlight
Tue 6:30 Hierarchical VAEs Know What They Don’t Know
Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
Spotlight
Tue 6:35 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco R Ruiz, Liping Liu
Spotlight
Tue 6:35 Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian Ober, Laurence Aitchison
Spotlight
Tue 6:35 Principal Component Hierarchy for Sparse Quadratic Programs
Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani
Spotlight
Tue 6:35 Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
Spotlight
Tue 6:35 Efficient Lottery Ticket Finding: Less Data is More
Zhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang
Spotlight
Tue 6:35 Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik
Spotlight
Tue 6:35 A Functional Perspective on Learning Symmetric Functions with Neural Networks
Aaron Zweig, Joan Bruna
Spotlight
Tue 6:40 Bayesian Deep Learning via Subnetwork Inference
Erik Daxberger, Eric Nalisnick, James Allingham, Javier Antorán, Jose Miguel Hernandez-Lobato
Spotlight
Tue 6:40 ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases
Stéphane d'Ascoli, Hugo Touvron, Matthew Leavitt, Ari Morcos, Giulio Biroli, Levent Sagun
Spotlight
Tue 6:40 Generative Video Transformer: Can Objects be the Words?
Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn
Spotlight
Tue 6:40 Thinking Like Transformers
Gail Weiss, Yoav Goldberg, Eran Yahav
Spotlight
Tue 6:40 Self Normalizing Flows
T. Anderson Keller, Jorn Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
Spotlight
Tue 6:45 Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
Johannes Klicpera, Marten Lienen, Stephan Günnemann
Spotlight
Tue 6:45 Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Wilson
Spotlight
Tue 6:45 Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks
Xuhui Fan, Bin Li, Yaqiong Li, Scott SIsson
Spotlight
Tue 6:45 On the Random Conjugate Kernel and Neural Tangent Kernel
Zhengmian Hu, Heng Huang
Spotlight
Tue 6:45 Provably Strict Generalisation Benefit for Equivariant Models
Bryn Elesedy, Sheheryar Zaidi
Spotlight
Tue 6:45 Generative Particle Variational Inference via Estimation of Functional Gradients
Neale Ratzlaff, Jerry Bai, Fuxin Li, Wei Xu
Oral
Tue 7:00 OmniNet: Omnidirectional Representations from Transformers
Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Don Metzler
Oral
Tue 7:00 Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders
Adeel Pervez, Efstratios Gavves
Oral Session
Tue 7:00 Deep Learning 1
Oral Session
Tue 7:00 Deep Learning Algorithms 4
Oral Session
Tue 7:00 Deep Learning Algorithms 3
Oral
Tue 7:00 Directional Graph Networks
Dominique Beaini, Saro Passaro, Vincent Létourneau, Will Hamilton, Gabriele Corso, Pietro Lió
Oral
Tue 7:00 Not All Memories are Created Equal: Learning to Forget by Expiring
Sainbayar Sukhbaatar, Dexter JU, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan
Spotlight
Tue 7:20 Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
Spotlight
Tue 7:20 Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size
Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak
Spotlight
Tue 7:20 Winograd Algorithm for AdderNet
Wenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen, Chunjing Xu, Yunhe Wang
Spotlight
Tue 7:20 Riemannian Convex Potential Maps
samuel cohen, Brandon Amos, Yaron Lipman
Spotlight
Tue 7:25 Perceiver: General Perception with Iterative Attention
Andrew Jaegle, Felix Axel Gimeno Gil, Andy Brock, Oriol Vinyals, Andrew Zisserman, Joao Carreira
Spotlight
Tue 7:25 LieTransformer: Equivariant Self-Attention for Lie Groups
Michael Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee-Whye Teh, Hyunjik Kim
Spotlight
Tue 7:25 E(n) Equivariant Graph Neural Networks
Víctor Garcia Satorras, Emiel Hoogeboom, Max Welling
Spotlight
Tue 7:25 Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
Spotlight
Tue 7:30 Synthesizer: Rethinking Self-Attention for Transformer Models
Yi Tay, Dara Bahri, Don Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng
Spotlight
Tue 7:30 Grid-Functioned Neural Networks
Javier Dehesa, Andrew Vidler, Julian Padget, Christof Lutteroth
Spotlight
Tue 7:30 "Hey, that's not an ODE": Faster ODE Adjoints via Seminorms
Patrick Kidger, Ricky T. Q. Chen, Terry Lyons
Spotlight
Tue 7:30 PixelTransformer: Sample Conditioned Signal Generation
Shubham Tulsiani, Abhinav Gupta
Spotlight
Tue 7:35 Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks
Maxwell M Aladago, Lorenzo Torresani
Spotlight
Tue 7:35 MSA Transformer
Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives
Spotlight
Tue 7:35 Graph Mixture Density Networks
Federico Errica, Davide Bacciu, Alessio Micheli
Spotlight
Tue 7:35 Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Sung Woo Park, Dong Wook Shu, Junseok Kwon
Spotlight
Tue 7:40 Momentum Residual Neural Networks
Michael Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré
Spotlight
Tue 7:40 What's in the Box? Exploring the Inner Life of Neural Networks with Robust Rules
Jonas Fischer, Anna Olah, Jilles Vreeken
Spotlight
Tue 7:40 Parallelizing Legendre Memory Unit Training
Narsimha Reddy Chilkuri, Chris Eliasmith
Spotlight
Tue 7:40 Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring, Zohar Yakhini, Yacov Hel-Or
Spotlight
Tue 7:40 Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond
Dennis Wei
Spotlight
Tue 7:45 Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto Surface
Baorui Ma, Zhizhong Han, Yushen Liu, Matthias Zwicker
Spotlight
Tue 7:45 Better Training using Weight-Constrained Stochastic Dynamics
Benedict Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos Storkey
Spotlight
Tue 7:45 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 Generative Adversarial Networks for Markovian Temporal Dynamics: Stochastic Continuous Data Generation
Sung Woo Park, Dong Wook Shu, Junseok Kwon
Poster
Tue 9:00 Neural Symbolic Regression that scales
Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurelien Lucchi, Giambattista Parascandolo
Poster
Tue 9:00 Leveraging Sparse Linear Layers for Debuggable Deep Networks
Eric Wong, Shibani Santurkar, Aleksander Madry
Poster
Tue 9:00 Attention is not all you need: pure attention loses rank doubly exponentially with depth
Yihe Dong, Jean-Baptiste Cordonnier, Andreas Loukas
Poster
Tue 9:00 A Probabilistic Approach to Neural Network Pruning
Xin Qian, Diego Klabjan
Poster
Tue 9:00 ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases
Stéphane d'Ascoli, Hugo Touvron, Matthew Leavitt, Ari Morcos, Giulio Biroli, Levent Sagun
Poster
Tue 9:00 What's in the Box? Exploring the Inner Life of Neural Networks with Robust Rules
Jonas Fischer, Anna Olah, Jilles Vreeken
Poster
Tue 9:00 Perceiver: General Perception with Iterative Attention
Andrew Jaegle, Felix Axel Gimeno Gil, Andy Brock, Oriol Vinyals, Andrew Zisserman, Joao Carreira
Poster
Tue 9:00 Self-Tuning for Data-Efficient Deep Learning
Ximei Wang, Jinghan Gao, Mingsheng Long, Jianmin Wang
Poster
Tue 9:00 "Hey, that's not an ODE": Faster ODE Adjoints via Seminorms
Patrick Kidger, Ricky T. Q. Chen, Terry Lyons
Poster
Tue 9:00 PixelTransformer: Sample Conditioned Signal Generation
Shubham Tulsiani, Abhinav Gupta
Poster
Tue 9:00 AutoSampling: Search for Effective Data Sampling Schedules
MING SUN, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui
Poster
Tue 9:00 LieTransformer: Equivariant Self-Attention for Lie Groups
Michael Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee-Whye Teh, Hyunjik Kim
Poster
Tue 9:00 What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov, Sharad Vikram, Matt Hoffman, Andrew Wilson
Poster
Tue 9:00 Autoencoder Image Interpolation by Shaping the Latent Space
Alon Oring, Zohar Yakhini, Yacov Hel-Or
Poster
Tue 9:00 Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
Johannes Klicpera, Marten Lienen, Stephan Günnemann
Poster
Tue 9:00 Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
Poster
Tue 9:00 Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size
Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak
Poster
Tue 9:00 Interpretable Stability Bounds for Spectral Graph Filters
Henry Kenlay, Dorina Thanou, Xiaowen Dong
Poster
Tue 9:00 Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, JING YU, Ce Zhang, Gao Huang, Yunhai Tong
Poster
Tue 9:00 Winograd Algorithm for AdderNet
Wenshuo Li, Hanting Chen, Mingqiang Huang, Xinghao Chen, Chunjing Xu, Yunhe Wang
Poster
Tue 9:00 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
Poster
Tue 9:00 Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco R Ruiz, Liping Liu
Poster
Tue 9:00 SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
Wuxinlin Cheng, Chenhui Deng, Zhiqiang Zhao, Yaohui Cai, Zhiru Zhang, Zhuo Feng
Poster
Tue 9:00 Generative Adversarial Transformers
Drew A. Hudson, Larry Zitnick
Poster
Tue 9:00 Provably Strict Generalisation Benefit for Equivariant Models
Bryn Elesedy, Sheheryar Zaidi
Poster
Tue 9:00 Relative Positional Encoding for Transformers with Linear Complexity
Antoine Liutkus, Ondřej Cífka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, Gaël RICHARD
Poster
Tue 9:00 Riemannian Convex Potential Maps
samuel cohen, Brandon Amos, Yaron Lipman
Poster
Tue 9:00 A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration
Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu
Poster
Tue 9:00 Efficient Differentiable Simulation of Articulated Bodies
Yi-Ling Qiao, Junbang Liang, Vladlen Koltun, Ming Lin
Poster
Tue 9:00 HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik
Poster
Tue 9:00 NeRF-VAE: A Geometry Aware 3D Scene Generative Model
Adam Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo J. Rezende
Poster
Tue 9:00 Neural-Pull: Learning Signed Distance Function from Point clouds by Learning to Pull Space onto Surface
Baorui Ma, Zhizhong Han, Yushen Liu, Matthias Zwicker
Poster
Tue 9:00 Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
Poster
Tue 9:00 Principal Component Hierarchy for Sparse Quadratic Programs
Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani
Poster
Tue 9:00 Sliced Iterative Normalizing Flows
Biwei Dai, Uros Seljak
Poster
Tue 9:00 PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization
Zhize Li, Hongyan Bao, Xiangliang Zhang, Peter Richtarik
Poster
Tue 9:00 Deep kernel processes
Laurence Aitchison, Adam Yang, Sebastian Ober
Poster
Tue 9:00 Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes
Sebastian Ober, Laurence Aitchison
Poster
Tue 9:00 Decision-Making Under Selective Labels: Optimal Finite-Domain Policies and Beyond
Dennis Wei
Poster
Tue 9:00 Slot Machines: Discovering Winning Combinations of Random Weights in Neural Networks
Maxwell M Aladago, Lorenzo Torresani
Poster
Tue 9:00 Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
Poster
Tue 9:00 Not All Memories are Created Equal: Learning to Forget by Expiring
Sainbayar Sukhbaatar, Dexter JU, Spencer Poff, Stephen Roller, Arthur Szlam, Jason Weston, Angela Fan
Poster
Tue 9:00 On Monotonic Linear Interpolation of Neural Network Parameters
James Lucas, Juhan Bae, Michael Zhang, Stanislav Fort, Richard Zemel, Roger Grosse
Poster
Tue 9:00 KNAS: Green Neural Architecture Search
Jingjing Xu, Liang Zhao, Junyang Lin, Rundong Gao, Xu SUN, Hongxia Yang
Poster
Tue 9:00 Generative Particle Variational Inference via Estimation of Functional Gradients
Neale Ratzlaff, Jerry Bai, Fuxin Li, Wei Xu
Poster
Tue 9:00 Neural Architecture Search without Training
Joe Mellor, Jack Turner, Amos Storkey, Elliot Crowley
Poster
Tue 9:00 E(n) Equivariant Graph Neural Networks
Víctor Garcia Satorras, Emiel Hoogeboom, Max Welling
Poster
Tue 9:00 Self Normalizing Flows
T. Anderson Keller, Jorn Peters, Priyank Jaini, Emiel Hoogeboom, Patrick Forré, Max Welling
Poster
Tue 9:00 Grid-Functioned Neural Networks
Javier Dehesa, Andrew Vidler, Julian Padget, Christof Lutteroth
Poster
Tue 9:00 Directional Graph Networks
Dominique Beaini, Saro Passaro, Vincent Létourneau, Will Hamilton, Gabriele Corso, Pietro Lió
Poster
Tue 9:00 OmniNet: Omnidirectional Representations from Transformers
Yi Tay, Mostafa Dehghani, Vamsi Aribandi, Jai Gupta, Philip Pham, Zhen Qin, Dara Bahri, Da-Cheng Juan, Don Metzler
Poster
Tue 9:00 Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation
Aurick Zhou, Sergey Levine
Poster
Tue 9:00 Synthesizer: Rethinking Self-Attention for Transformer Models
Yi Tay, Dara Bahri, Don Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng
Poster
Tue 9:00 Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Will Grathwohl, Kevin Swersky, Milad Hashemi, David Duvenaud, Chris Maddison
Poster
Tue 9:00 Let's Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework
Floris Geerts, Filip Mazowiecki, Guillermo Perez
Poster
Tue 9:00 Preferential Temporal Difference Learning
Nishanth Anand, Doina Precup
Poster
Tue 9:00 Spectral Smoothing Unveils Phase Transitions in Hierarchical Variational Autoencoders
Adeel Pervez, Efstratios Gavves
Poster
Tue 9:00 Principled Simplicial Neural Networks for Trajectory Prediction
Mitch Roddenberry, Nicholas Glaze, Santiago Segarra
Poster
Tue 9:00 Efficient Lottery Ticket Finding: Less Data is More
Zhenyu Zhang, Xuxi Chen, Tianlong Chen, Zhangyang Wang
Poster
Tue 9:00 Thinking Like Transformers
Gail Weiss, Yoav Goldberg, Eran Yahav
Poster
Tue 9:00 GraphDF: A Discrete Flow Model for Molecular Graph Generation
Youzhi Luo, Keqiang Yan, Shuiwang Ji
Poster
Tue 9:00 Poisson-Randomised DirBN: Large Mutation is Needed in Dirichlet Belief Networks
Xuhui Fan, Bin Li, Yaqiong Li, Scott SIsson
Poster
Tue 9:00 Generative Video Transformer: Can Objects be the Words?
Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn
Poster
Tue 9:00 Momentum Residual Neural Networks
Michael Sander, Pierre Ablin, Mathieu Blondel, Gabriel Peyré
Poster
Tue 9:00 Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
Alex Immer, Matthias Bauer, Vincent Fortuin, Gunnar Ratsch, Khan Emtiyaz
Poster
Tue 9:00 A Functional Perspective on Learning Symmetric Functions with Neural Networks
Aaron Zweig, Joan Bruna
Poster
Tue 9:00 Bayesian Deep Learning via Subnetwork Inference
Erik Daxberger, Eric Nalisnick, James Allingham, Javier Antorán, Jose Miguel Hernandez-Lobato
Poster
Tue 9:00 On the Random Conjugate Kernel and Neural Tangent Kernel
Zhengmian Hu, Heng Huang
Poster
Tue 9:00 Parallelizing Legendre Memory Unit Training
Narsimha Reddy Chilkuri, Chris Eliasmith
Poster
Tue 9:00 Improved Denoising Diffusion Probabilistic Models
Alexander Nichol, Prafulla Dhariwal
Poster
Tue 9:00 Better Training using Weight-Constrained Stochastic Dynamics
Benedict Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos Storkey
Poster
Tue 9:00 Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Wilson
Poster
Tue 9:00 Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
Eli Meirom, Haggai Maron, Shie Mannor, Gal Chechik
Poster
Tue 9:00 Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
Zeke Xie, Li Yuan, Zhanxing Zhu, Masashi Sugiyama
Poster
Tue 9:00 Graph Mixture Density Networks
Federico Errica, Davide Bacciu, Alessio Micheli
Poster
Tue 9:00 MSA Transformer
Roshan Rao, Jason Liu, Robert Verkuil, Joshua Meier, John Canny, Pieter Abbeel, Tom Sercu, Alexander Rives
Poster
Tue 9:00 Towards Understanding Learning in Neural Networks with Linear Teachers
Roei Sarussi, Alon Brutzkus, Amir Globerson
Poster
Tue 9:00 Connecting Sphere Manifolds Hierarchically for Regularization
Damien Scieur, Youngsung Kim
Poster
Tue 9:00 Zoo-Tuning: Adaptive Transfer from A Zoo of Models
Yang Shu, Zhi Kou, Zhangjie Cao, Jianmin Wang, Mingsheng Long
Poster
Tue 9:00 A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang
Poster
Tue 9:00 UnICORNN: A recurrent model for learning very long time dependencies
T. Konstantin Rusch, Siddhartha Mishra
Poster
Tue 9:00 Hierarchical VAEs Know What They Don’t Know
Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
Oral Session
Tue 17:00 Deep Learning 2
Oral
Tue 17:00 A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
Marc Finzi, Max Welling, Andrew Wilson
Oral Session
Tue 17:00 Deep Learning Algorithms 5
Oral
Tue 17:00 Characterizing Structural Regularities of Labeled Data in Overparameterized Models
Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Mike Mozer
Oral Session
Tue 17:00 Deep Learning Algorithms 6
Oral
Tue 17:00 NeRF-VAE: A Geometry Aware 3D Scene Generative Model
Adam Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo J. Rezende
Spotlight
Tue 17:20 Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki
Spotlight
Tue 17:20 Stabilizing Equilibrium Models by Jacobian Regularization
Shaojie Bai, Vladlen Koltun, Zico Kolter
Spotlight
Tue 17:25 Adapting to Delays and Data in Adversarial Multi-Armed Bandits
András György, Pooria Joulani
Spotlight
Tue 17:25 On the Predictability of Pruning Across Scales
Jonathan Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit
Spotlight
Tue 17:25 Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
Spotlight
Tue 17:25 Towards Domain-Agnostic Contrastive Learning
Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc Le
Spotlight
Tue 17:25 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
Spotlight
Tue 17:25 Quantization Algorithms for Random Fourier Features
Xiaoyun Li, Ping Li
Spotlight
Tue 17:30 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Spotlight
Tue 17:30 Structured Convolutional Kernel Networks for Airline Crew Scheduling
Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien
Spotlight
Tue 17:30 Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang
Spotlight
Tue 17:30 Improved Contrastive Divergence Training of Energy-Based Models
Yilun Du, Shuang Li, Josh Tenenbaum, Igor Mordatch
Spotlight
Tue 17:30 Joining datasets via data augmentation in the label space for neural networks
Jake Zhao Zhao, Mingfeng Ou, linji Xue, Yunkai Cui, Sai Wu, Gang Chen
Spotlight
Tue 17:35 Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
Spotlight
Tue 17:35 Equivariant message passing for the prediction of tensorial properties and molecular spectra
Kristof T Schütt, Oliver Unke, Michael Gastegger
Spotlight
Tue 17:35 LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning
Yuhuai Wu, Markus Rabe, Wenda Li, Jimmy Ba, Roger Grosse, Christian Szegedy
Spotlight
Tue 17:40 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Spotlight
Tue 17:40 Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset
Ilan Price, Jared Tanner
Spotlight
Tue 17:40 Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies.
Denis Lukovnikov, Asja Fischer
Spotlight
Tue 17:45 Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari
Spotlight
Tue 17:45 Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily Zhang, Mark Goldstein, Rajesh Ranganath
Oral Session
Tue 18:00 Deep Learning Algorithms and Applications
Oral
Tue 18:00 Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, Peter Battaglia
Oral
Tue 18:00 Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Paul Vicol, Luke Metz, Jascha Sohl-Dickstein
Spotlight
Tue 18:20 An Identifiable Double VAE For Disentangled Representations
Graziano Mita, Maurizio Filippone, Pietro Michiardi
Spotlight
Tue 18:20 The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu
Spotlight
Tue 18:20 Weight-covariance alignment for adversarially robust neural networks
Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy Hospedales
Spotlight
Tue 18:25 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Spotlight
Tue 18:30 LAMDA: Label Matching Deep Domain Adaptation
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
Spotlight
Tue 18:30 On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan Chatapuram Krishnan
Spotlight
Tue 18:35 Scalable Normalizing Flows for Permutation Invariant Densities
Marin Biloš, Stephan Günnemann
Spotlight
Tue 18:35 A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance
Minhui Huang, Shiqian Ma, Lifeng Lai
Spotlight
Tue 18:40 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
Spotlight
Tue 18:45 Zero-Shot Text-to-Image Generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
Oral
Tue 19:00 AlphaNet: Improved Training of Supernets with Alpha-Divergence
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra
Oral Session
Tue 19:00 Deep Learning Algorithms 8
Oral
Tue 19:00 Out-of-Distribution Generalization via Risk Extrapolation (REx)
David Krueger, Ethan Caballero, Jörn Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, Aaron Courville
Oral Session
Tue 19:00 Deep Learning Algorithms 7
Oral
Tue 19:00 Just Train Twice: Improving Group Robustness without Training Group Information
Evan Liu, Behzad Haghgoo, Annie Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn
Spotlight
Tue 19:20 Catformer: Designing Stable Transformers via Sensitivity Analysis
Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Re, Chelsea Finn, Percy Liang
Spotlight
Tue 19:25 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
Spotlight
Tue 19:25 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Spotlight
Tue 19:25 A Receptor Skeleton for Capsule Neural Networks
Jintai Chen, Hongyun Yu, Chengde Qian, Danny Z Chen, Jian Wu
Spotlight
Tue 19:25 On Explainability of Graph Neural Networks via Subgraph Explorations
Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji
Spotlight
Tue 19:30 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
Spotlight
Tue 19:30 Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Taufik Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
Spotlight
Tue 19:30 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek
Spotlight
Tue 19:30 Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein
Spotlight
Tue 19:35 Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein
Spotlight
Tue 19:35 K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets
Xiu Su, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
Spotlight
Tue 19:40 High-Performance Large-Scale Image Recognition Without Normalization
Andy Brock, Soham De, Samuel Smith, Karen Simonyan
Spotlight
Tue 19:40 Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Mike Mozer
Spotlight
Tue 19:40 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Spotlight
Tue 19:45 Ditto: Fair and Robust Federated Learning Through Personalization
Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith
Spotlight
Tue 19:45 Data augmentation for deep learning based accelerated MRI reconstruction with limited data
Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
Spotlight
Tue 19:45 Lipschitz normalization for self-attention layers with application to graph neural networks
George Dasoulas, Kevin Scaman, Aladin Virmaux
Spotlight
Tue 19:45 Neural Symbolic Regression that scales
Luca Biggio, Tommaso Bendinelli, Alexander Neitz, Aurelien Lucchi, Giambattista Parascandolo
Poster
Tue 21:00 Signatured Deep Fictitious Play for Mean Field Games with Common Noise
Ming Min, Ruimeng Hu
Poster
Tue 21:00 AlphaNet: Improved Training of Supernets with Alpha-Divergence
Dilin Wang, Chengyue Gong, Meng Li, Qiang Liu, Vikas Chandra
Poster
Tue 21:00 Quantization Algorithms for Random Fourier Features
Xiaoyun Li, Ping Li
Poster
Tue 21:00 Structured Convolutional Kernel Networks for Airline Crew Scheduling
Yassine Yaakoubi, Francois Soumis, Simon Lacoste-Julien
Poster
Tue 21:00 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Poster
Tue 21:00 Out-of-Distribution Generalization via Risk Extrapolation (REx)
David Krueger, Ethan Caballero, Jörn Jacobsen, Amy Zhang, Jonathan Binas, Dinghuai Zhang, Remi Le Priol, Aaron Courville
Poster
Tue 21:00 Learning Neural Network Subspaces
Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari
Poster
Tue 21:00 Deep Generative Learning via Schrödinger Bridge
Gefei Wang, Yuling Jiao, Qian Xu, Yang Wang, Can Yang
Poster
Tue 21:00 K-shot NAS: Learnable Weight-Sharing for NAS with K-shot Supernets
Xiu Su, Shan You, Mingkai Zheng, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
Poster
Tue 21:00 Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein
Poster
Tue 21:00 Dense for the Price of Sparse: Improved Performance of Sparsely Initialized Networks via a Subspace Offset
Ilan Price, Jared Tanner
Poster
Tue 21:00 Improved Contrastive Divergence Training of Energy-Based Models
Yilun Du, Shuang Li, Josh Tenenbaum, Igor Mordatch
Poster
Tue 21:00 LAMDA: Label Matching Deep Domain Adaptation
Trung Le, Tuan Nguyen, Nhat Ho, Hung Bui, Dinh Phung
Poster
Tue 21:00 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics
Vivek Jayaram, John Thickstun
Poster
Tue 21:00 Data augmentation for deep learning based accelerated MRI reconstruction with limited data
Zalan Fabian, Reinhard Heckel, Mahdi Soltanolkotabi
Poster
Tue 21:00 Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Fan Bao, Taufik Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
Poster
Tue 21:00 Scalable Normalizing Flows for Permutation Invariant Densities
Marin Biloš, Stephan Günnemann
Poster
Tue 21:00 An Identifiable Double VAE For Disentangled Representations
Graziano Mita, Maurizio Filippone, Pietro Michiardi
Poster
Tue 21:00 Weight-covariance alignment for adversarially robust neural networks
Panagiotis Eustratiadis, Henry Gouk, Da Li, Timothy Hospedales
Poster
Tue 21:00 Towards Domain-Agnostic Contrastive Learning
Vikas Verma, Thang Luong, Kenji Kawaguchi, Hieu Pham, Quoc Le
Poster
Tue 21:00 Ditto: Fair and Robust Federated Learning Through Personalization
Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith
Poster
Tue 21:00 A Bit More Bayesian: Domain-Invariant Learning with Uncertainty
Zehao Xiao, Jiayi Shen, Xiantong Zhen, Ling Shao, Cees Snoek
Poster
Tue 21:00 Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein
Poster
Tue 21:00 A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance
Minhui Huang, Shiqian Ma, Lifeng Lai
Poster
Tue 21:00 Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies.
Denis Lukovnikov, Asja Fischer
Poster
Tue 21:00 Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily Zhang, Mark Goldstein, Rajesh Ranganath
Poster
Tue 21:00 Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not?
Ning Liu, Geng Yuan, Zhengping Che, Xuan Shen, Xiaolong Ma, Qing Jin, Jian Ren, Jian Tang, Sijia Liu, Yanzhi Wang
Poster
Tue 21:00 On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan Chatapuram Krishnan
Poster
Tue 21:00 Zero-Shot Text-to-Image Generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, Ilya Sutskever
Poster
Tue 21:00 LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning
Yuhuai Wu, Markus Rabe, Wenda Li, Jimmy Ba, Roger Grosse, Christian Szegedy
Poster
Tue 21:00 GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
Poster
Tue 21:00 A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
Marc Finzi, Max Welling, Andrew Wilson
Poster
Tue 21:00 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
Poster
Tue 21:00 Lipschitz normalization for self-attention layers with application to graph neural networks
George Dasoulas, Kevin Scaman, Aladin Virmaux
Poster
Tue 21:00 High-Performance Large-Scale Image Recognition Without Normalization
Andy Brock, Soham De, Samuel Smith, Karen Simonyan
Poster
Tue 21:00 A Receptor Skeleton for Capsule Neural Networks
Jintai Chen, Hongyun Yu, Chengde Qian, Danny Z Chen, Jian Wu
Poster
Tue 21:00 Soft then Hard: Rethinking the Quantization in Neural Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Zhibo Chen
Poster
Tue 21:00 The Heavy-Tail Phenomenon in SGD
Mert Gurbuzbalaban, Umut Simsekli, Lingjiong Zhu
Poster
Tue 21:00 Characterizing Structural Regularities of Labeled Data in Overparameterized Models
Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Mike Mozer
Poster
Tue 21:00 Stabilizing Equilibrium Models by Jacobian Regularization
Shaojie Bai, Vladlen Koltun, Zico Kolter
Poster
Tue 21:00 Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding
Akira Nakagawa, Keizo Kato, Taiji Suzuki
Poster
Tue 21:00 Catformer: Designing Stable Transformers via Sensitivity Analysis
Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Re, Chelsea Finn, Percy Liang
Poster
Tue 21:00 On Explainability of Graph Neural Networks via Subgraph Explorations
Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji
Poster
Tue 21:00 Partially Observed Exchangeable Modeling
Yang Li, Junier Oliva
Poster
Tue 21:00 Equivariant message passing for the prediction of tensorial properties and molecular spectra
Kristof T Schütt, Oliver Unke, Michael Gastegger
Poster
Tue 21:00 RRL: Resnet as representation for Reinforcement Learning
Rutav Shah, Vikash Kumar
Poster
Tue 21:00 Unbiased Gradient Estimation in Unrolled Computation Graphs with Persistent Evolution Strategies
Paul Vicol, Luke Metz, Jascha Sohl-Dickstein
Poster
Tue 21:00 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Poster
Tue 21:00 On the Predictability of Pruning Across Scales
Jonathan Rosenfeld, Jonathan Frankle, Michael Carbin, Nir Shavit
Poster
Tue 21:00 Generating images with sparse representations
Charlie Nash, Jacob Menick, Sander Dieleman, Peter Battaglia
Poster
Tue 21:00 Joining datasets via data augmentation in the label space for neural networks
Jake Zhao Zhao, Mingfeng Ou, linji Xue, Yunkai Cui, Sai Wu, Gang Chen
Poster
Tue 21:00 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
Poster
Tue 21:00 Just Train Twice: Improving Group Robustness without Training Group Information
Evan Liu, Behzad Haghgoo, Annie Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn
Oral Session
Wed 5:00 Deep Learning Theory 2
Oral
Wed 5:00 On Energy-Based Models with Overparametrized Shallow Neural Networks
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna
Spotlight
Wed 5:20 Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller
Spotlight
Wed 5:20 Uncertainty Principles of Encoding GANs
TaiGe Feng, Zhouchen Lin, jiapeng zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha
Spotlight
Wed 5:25 On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths
Quynh Nguyen
Spotlight
Wed 5:30 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Spotlight
Wed 5:30 Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido Montufar
Spotlight
Wed 5:35 Functional Space Analysis of Local GAN Convergence
Valentin Khrulkov, Artem Babenko, Ivan Oseledets
Spotlight
Wed 5:35 TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
Spotlight
Wed 5:35 Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing
Yuan Deng, Sébastien Lahaie, Vahab Mirrokni, Song Zuo
Spotlight
Wed 5:40 Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models
Zitong Yang, Yu Bai, Song Mei
Spotlight
Wed 5:40 On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama, Taiji Suzuki
Spotlight
Wed 5:45 Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei, Yuan Cao, Quanquan Gu
Spotlight
Wed 5:45 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Spotlight
Wed 6:20 Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model
Zi Wang
Spotlight
Wed 6:25 A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network
Jun-Kun Wang, Chi-Heng Lin, Jake Abernethy
Spotlight
Wed 6:25 Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos Ruiz, Paul Grigas, Zheng Wen
Spotlight
Wed 6:30 Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M Schmidt, Frank Schneider, Philipp Hennig
Spotlight
Wed 6:30 Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics
Avik Pal, Yingbo Ma, Viral Shah, Christopher Rackauckas
Spotlight
Wed 6:35 Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Emtiyaz, Mark Schmidt
Spotlight
Wed 6:40 Learning from Nested Data with Ornstein Auto-Encoders
Youngwon Choi, Sungdong Lee, Joong-Ho (Johann) Won
Oral
Wed 7:00 Measuring Robustness in Deep Learning Based Compressive Sensing
Mohammad Zalbagi Darestani, Akshay Chaudhari, Reinhard Heckel
Affinity Workshop
Wed 7:00 Invited Talk #1 - Evaluating approximate inference for BNNs
Yingzhen Li
Oral Session
Wed 7:00 Deep Learning Theory 3
Oral
Wed 7:00 On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake Woodworth, Nati Srebro, Amir Globerson, Daniel Soudry
Spotlight
Wed 7:20 A statistical perspective on distillation
Aditya Menon, Ankit Singh Rawat, Sashank Jakkam Reddi, Seungyeon Kim, Sanjiv Kumar
Spotlight
Wed 7:25 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Spotlight
Wed 7:25 The Lipschitz Constant of Self-Attention
Hyunjik Kim, George Papamakarios, Andriy Mnih
Spotlight
Wed 7:30 Revealing the Structure of Deep Neural Networks via Convex Duality
Tolga Ergen, Mert Pilanci
Spotlight
Wed 7:30 SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
Lingxiao YANG, Ru-Yuan Zhang, Lida LI, Xiaohua Xie
Spotlight
Wed 7:35 Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
Spotlight
Wed 7:35 Active Deep Probabilistic Subsampling
Hans van Gorp, Iris Huijben, Bastiaan Veeling, Nicola Pezzotti, Ruud J. G. van Sloun
Spotlight
Wed 7:35 Large-Scale Multi-Agent Deep FBSDEs
Tianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos Theodorou
Spotlight
Wed 7:40 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Spotlight
Wed 7:40 Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li
Spotlight
Wed 7:45 Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You, Xiaodi Wu
Spotlight
Wed 7:45 The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning
Roberto Bondesan, Max Welling
Poster
Wed 9:00 On Energy-Based Models with Overparametrized Shallow Neural Networks
Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna
Poster
Wed 9:00 Accelerating Safe Reinforcement Learning with Constraint-mismatched Baseline Policies
Jimmy Yang, Justinian Rosca, Karthik Narasimhan, Peter Ramadge
Poster
Wed 9:00 Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li
Poster
Wed 9:00 Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M Schmidt, Frank Schneider, Philipp Hennig
Poster
Wed 9:00 The Lipschitz Constant of Self-Attention
Hyunjik Kim, George Papamakarios, Andriy Mnih
Poster
Wed 9:00 On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths
Quynh Nguyen
Poster
Wed 9:00 Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
Quynh Nguyen, Marco Mondelli, Guido Montufar
Poster
Wed 9:00 SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks
Lingxiao YANG, Ru-Yuan Zhang, Lida LI, Xiaohua Xie
Poster
Wed 9:00 Large-Scale Multi-Agent Deep FBSDEs
Tianrong Chen, Ziyi Wang, Ioannis Exarchos, Evangelos Theodorou
Poster
Wed 9:00 Debiasing a First-order Heuristic for Approximate Bi-level Optimization
Valerii Likhosherstov, Xingyou Song, Krzysztof Choromanski, Jared Quincy Davis, Adrian Weller
Poster
Wed 9:00 Uncertainty Principles of Encoding GANs
TaiGe Feng, Zhouchen Lin, jiapeng zhu, Deli Zhao, Jingren Zhou, Zheng-Jun Zha
Poster
Wed 9:00 A statistical perspective on distillation
Aditya Menon, Ankit Singh Rawat, Sashank Jakkam Reddi, Seungyeon Kim, Sanjiv Kumar
Poster
Wed 9:00 The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning
Roberto Bondesan, Max Welling
Poster
Wed 9:00 On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
Shunta Akiyama, Taiji Suzuki
Poster
Wed 9:00 How to Learn when Data Reacts to Your Model: Performative Gradient Descent
Zachary Izzo, Lexing Ying, James Zou
Poster
Wed 9:00 Representational aspects of depth and conditioning in normalizing flows
Frederic Koehler, Viraj Mehta, Andrej Risteski
Poster
Wed 9:00 Active Deep Probabilistic Subsampling
Hans van Gorp, Iris Huijben, Bastiaan Veeling, Nicola Pezzotti, Ruud J. G. van Sloun
Poster
Wed 9:00 Prior Image-Constrained Reconstruction using Style-Based Generative Models
Varun A. Kelkar, Mark Anastasio
Poster
Wed 9:00 Learning from Nested Data with Ornstein Auto-Encoders
Youngwon Choi, Sungdong Lee, Joong-Ho (Johann) Won
Poster
Wed 9:00 Active Feature Acquisition with Generative Surrogate Models
Yang Li, Junier Oliva
Poster
Wed 9:00 Tractable structured natural-gradient descent using local parameterizations
Wu Lin, Frank Nielsen, Khan Emtiyaz, Mark Schmidt
Poster
Wed 9:00 Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos Ruiz, Paul Grigas, Zheng Wen
Poster
Wed 9:00 Measuring Robustness in Deep Learning Based Compressive Sensing
Mohammad Zalbagi Darestani, Akshay Chaudhari, Reinhard Heckel
Poster
Wed 9:00 Revenue-Incentive Tradeoffs in Dynamic Reserve Pricing
Yuan Deng, Sébastien Lahaie, Vahab Mirrokni, Song Zuo
Poster
Wed 9:00 Revealing the Structure of Deep Neural Networks via Convex Duality
Tolga Ergen, Mert Pilanci
Poster
Wed 9:00 Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models
Zitong Yang, Yu Bai, Song Mei
Poster
Wed 9:00 Exponentially Many Local Minima in Quantum Neural Networks
Xuchen You, Xiaodi Wu
Poster
Wed 9:00 Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei, Yuan Cao, Quanquan Gu
Poster
Wed 9:00 On the Implicit Bias of Initialization Shape: Beyond Infinitesimal Mirror Descent
Shahar Azulay, Edward Moroshko, Mor Shpigel Nacson, Blake Woodworth, Nati Srebro, Amir Globerson, Daniel Soudry
Poster
Wed 9:00 A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network
Jun-Kun Wang, Chi-Heng Lin, Jake Abernethy
Poster
Wed 9:00 Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics
Avik Pal, Yingbo Ma, Viral Shah, Christopher Rackauckas
Poster
Wed 9:00 Zero-Shot Knowledge Distillation from a Decision-Based Black-Box Model
Zi Wang
Poster
Wed 9:00 TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
Poster
Wed 9:00 Functional Space Analysis of Local GAN Convergence
Valentin Khrulkov, Artem Babenko, Ivan Oseledets
Affinity Workshop
Wed 16:25 Breakout Session 3.1: Does your model know what it doesn’t know? Uncertainty estimation and out-of-distribution (OOD) detection in deep learning
Oral
Wed 17:00 Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
Oral
Wed 17:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Oral Session
Wed 17:00 Deep Learning Theory 4
Oral Session
Wed 17:00 Deep Learning Optimization
Spotlight
Wed 17:20 Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue
Spotlight
Wed 17:20 Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
Alexander D Camuto, Xiaoyu Wang, Lingjiong Zhu, Christopher Holmes, Mert Gurbuzbalaban, Umut Simsekli
Spotlight
Wed 17:25 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
Spotlight
Wed 17:25 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Spotlight
Wed 17:30 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Spotlight
Wed 17:30 Selfish Sparse RNN Training
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
Spotlight
Wed 17:30 FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis
Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
Spotlight
Wed 17:35 Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization
Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J Geras
Spotlight
Wed 17:35 Improved OOD Generalization via Adversarial Training and Pretraing
Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma
Spotlight
Wed 17:40 WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, TaeHo Yoon, Sehyun Kwon, Ernest Ryu
Spotlight
Wed 17:40 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
Tao Lin, Praneeth Karimireddy, Sebastian Stich, Martin Jaggi
Spotlight
Wed 17:40 How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation
Ali Akbari, Muhammad Awais, Manijeh Bashar, Josef Kittler
Spotlight
Wed 17:45 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Spotlight
Wed 17:45 Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
Salma Tarmoun, Guilherme Franca, Benjamin Haeffele, Rene Vidal
Spotlight
Wed 17:45 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Oral
Wed 18:00 RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton
Oral Session
Wed 18:00 Deep Learning Theory 5
Oral
Wed 18:00 Dissecting Supervised Constrastive Learning
Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt
Affinity Workshop
Wed 18:00 Invited Talk #4 - Errors are a crucial part of dialogue
luciana.benotti
Spotlight
Wed 18:20 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda
Spotlight
Wed 18:20 KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Ashok Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
Spotlight
Wed 18:25 Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward Hu
Spotlight
Wed 18:30 Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea
Spotlight
Wed 18:30 Scaling Properties of Deep Residual Networks
Alain-Sam Cohen, Rama Cont, Alain Rossier, Renyuan Xu
Spotlight
Wed 18:30 Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
Yuzhou Chen, Ignacio Segovia Dominguez, Yulia R Gel
Spotlight
Wed 18:35 Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Spotlight
Wed 18:35 Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach
Spotlight
Wed 18:40 A Novel Method to Solve Neural Knapsack Problems
Duanshun Li, Jing Liu, Dongeun Lee, Ali S. Mazloom, Giridhar Kaushik , Kookjin Lee, Noseong Park
Spotlight
Wed 18:40 Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin
Spotlight
Wed 18:45 Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication
Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Tae Hyun Cho, Jungwoo Lee
Spotlight
Wed 18:45 Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Oral
Wed 19:00 RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates
Spotlight
Wed 19:00 Deep Latent Graph Matching
Tianshu Yu, Runzhong Wang, Junchi Yan, baoxin Li
Oral
Wed 19:00 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville
Spotlight
Wed 19:10 Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
Zhaowei Zhu, Yiwen Song, Yang Liu
Spotlight
Wed 19:25 Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang
Spotlight
Wed 19:25 SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun
Spotlight
Wed 19:25 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Spotlight
Wed 19:25 Sparsity-Agnostic Lasso Bandit
Min-hwan Oh, Garud Iyengar, Assaf Zeevi
Spotlight
Wed 19:30 ACE: Explaining cluster from an adversarial perspective
Yang Lu, Timothy C Yu, Giancarlo Bonora, William Stafford Noble
Spotlight
Wed 19:30 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Spotlight
Wed 19:30 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Spotlight
Wed 19:30 Neural SDEs as Infinite-Dimensional GANs
Patrick Kidger, James Foster, Xuechen Li, Terry Lyons
Spotlight
Wed 19:30 HyperHyperNetwork for the Design of Antenna Arrays
Shahar Lutati, Lior Wolf
Spotlight
Wed 19:35 Dropout: Explicit Forms and Capacity Control
Raman Arora, Peter Bartlett, Poorya Mianjy, Nati Srebro
Spotlight
Wed 19:40 Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving
Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon
Spotlight
Wed 19:45 Learning Generalized Intersection Over Union for Dense Pixelwise Prediction
Jiaqian Yu, Jingtao Xu, Yiwei Chen, Weiming Li, Qiang Wang, ByungIn Yoo, Jae-Joon Han
Spotlight
Wed 19:45 Interpreting and Disentangling Feature Components of Various Complexity from DNNs
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
Poster
Wed 21:00 Learning Generalized Intersection Over Union for Dense Pixelwise Prediction
Jiaqian Yu, Jingtao Xu, Yiwei Chen, Weiming Li, Qiang Wang, ByungIn Yoo, Jae-Joon Han
Poster
Wed 21:00 Contrastive Learning Inverts the Data Generating Process
Roland S. Zimmermann, Yash Sharma, Steffen Schneider, Matthias Bethge, Wieland Brendel
Poster
Wed 21:00 How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation
Ali Akbari, Muhammad Awais, Manijeh Bashar, Josef Kittler
Poster
Wed 21:00 Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
Salma Tarmoun, Guilherme Franca, Benjamin Haeffele, Rene Vidal
Poster
Wed 21:00 FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis
Baihe Huang, Xiaoxiao Li, Zhao Song, Xin Yang
Poster
Wed 21:00 Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
Zhaowei Zhu, Yiwen Song, Yang Liu
Poster
Wed 21:00 Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron Courville
Poster
Wed 21:00 Noise and Fluctuation of Finite Learning Rate Stochastic Gradient Descent
Kangqiao Liu, Liu Ziyin, Masahito Ueda
Poster
Wed 21:00 Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving
Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon
Poster
Wed 21:00 Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
Yuzhou Chen, Ignacio Segovia Dominguez, Yulia R Gel
Poster
Wed 21:00 Scaling Properties of Deep Residual Networks
Alain-Sam Cohen, Rama Cont, Alain Rossier, Renyuan Xu
Poster
Wed 21:00 Selfish Sparse RNN Training
Shiwei Liu, Decebal Constantin Mocanu, Yulong Pei, Mykola Pechenizkiy
Poster
Wed 21:00 Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward Hu
Poster
Wed 21:00 Consensus Control for Decentralized Deep Learning
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian Stich
Poster
Wed 21:00 Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
Poster
Wed 21:00 A Novel Method to Solve Neural Knapsack Problems
Duanshun Li, Jing Liu, Dongeun Lee, Ali S. Mazloom, Giridhar Kaushik , Kookjin Lee, Noseong Park
Poster
Wed 21:00 Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication
Sangwoo Hong, Heecheol Yang, Youngseok Yoon, Tae Hyun Cho, Jungwoo Lee
Poster
Wed 21:00 Understanding self-supervised learning dynamics without contrastive pairs
Yuandong Tian, Xinlei Chen, Surya Ganguli
Poster
Wed 21:00 RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates
Poster
Wed 21:00 Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Mike Mozer
Poster
Wed 21:00 Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
Poster
Wed 21:00 Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Poster
Wed 21:00 Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin
Poster
Wed 21:00 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
Tao Lin, Praneeth Karimireddy, Sebastian Stich, Martin Jaggi
Poster
Wed 21:00 Trees with Attention for Set Prediction Tasks
Roy Hirsch, Ran Gilad-Bachrach
Poster
Wed 21:00 Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections
Alexander D Camuto, Xiaoyu Wang, Lingjiong Zhu, Christopher Holmes, Mert Gurbuzbalaban, Umut Simsekli
Poster
Wed 21:00 Dropout: Explicit Forms and Capacity Control
Raman Arora, Peter Bartlett, Poorya Mianjy, Nati Srebro
Poster
Wed 21:00 Understanding Noise Injection in GANs
TaiGe Feng, Deli Zhao, Zheng-Jun Zha
Poster
Wed 21:00 ACE: Explaining cluster from an adversarial perspective
Yang Lu, Timothy C Yu, Giancarlo Bonora, William Stafford Noble
Poster
Wed 21:00 Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister, Yisong Yue
Poster
Wed 21:00 Deep Latent Graph Matching
Tianshu Yu, Runzhong Wang, Junchi Yan, baoxin Li
Poster
Wed 21:00 Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization
Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J Geras
Poster
Wed 21:00 Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training
Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy
Poster
Wed 21:00 RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg, Sivaraman Balakrishnan, Zico Kolter, Zachary Lipton
Poster
Wed 21:00 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Poster
Wed 21:00 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
Poster
Wed 21:00 Interpreting and Disentangling Feature Components of Various Complexity from DNNs
Jie Ren, Mingjie Li, Zexu Liu, Quanshi Zhang
Poster
Wed 21:00 WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points
Albert No, TaeHo Yoon, Sehyun Kwon, Ernest Ryu
Poster
Wed 21:00 Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances
Berfin Simsek, François Ged, Arthur Jacot, Francesco Spadaro, Clement Hongler, Wulfram Gerstner, Johanni Brea
Poster
Wed 21:00 KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning
Ashok Makkuva, Xiyang Liu, Mohammad Vahid Jamali, Hessam Mahdavifar, Sewoong Oh, Pramod Viswanath
Poster
Wed 21:00 SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun
Poster
Wed 21:00 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Poster
Wed 21:00 Improved OOD Generalization via Adversarial Training and Pretraing
Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhiming Ma
Poster
Wed 21:00 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Poster
Wed 21:00 Neural SDEs as Infinite-Dimensional GANs
Patrick Kidger, James Foster, Xuechen Li, Terry Lyons
Poster
Wed 21:00 Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang
Poster
Wed 21:00 Dissecting Supervised Constrastive Learning
Florian Graf, Christoph Hofer, Marc Niethammer, Roland Kwitt
Poster
Wed 21:00 HyperHyperNetwork for the Design of Antenna Arrays
Shahar Lutati, Lior Wolf
Oral
Thu 5:00 Tilting the playing field: Dynamical loss functions for machine learning
Miguel Ruiz Garcia, Ge Zhang, Samuel Schoenholz, Andrea Liu
Oral
Thu 5:00 Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee
Oral
Thu 5:00 Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig
Oral Session
Thu 5:00 Deep Learning Theory 6
Spotlight
Thu 5:20 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Spotlight
Thu 5:20 GRAND: Graph Neural Diffusion
Ben Chamberlain, James Rowbottom, Maria Gorinova, Michael Bronstein, Stefan Webb, Emanuele Rossi
Spotlight
Thu 5:25 On Linear Identifiability of Learned Representations
Geoffrey Roeder, Luke Metz, Durk Kingma
Spotlight
Thu 5:25 Implicit Bias of Linear RNNs
Melika Emami, Moji Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson Fletcher
Spotlight
Thu 5:30 Analyzing the tree-layer structure of Deep Forests
Ludovic Arnould, Claire Boyer, Erwan Scornet
Spotlight
Thu 5:30 Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodola
Spotlight
Thu 5:35 A Collective Learning Framework to Boost GNN Expressiveness for Node Classification
Mengyue Hang, Jennifer Neville, Bruno Ribeiro
Spotlight
Thu 5:35 Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
Eran Malach, Pritish Kamath, Emmanuel Abbe, Nati Srebro
Spotlight
Thu 5:35 Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer
Seungwon Lee, Sima Behpour, Eric Eaton
Spotlight
Thu 5:40 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Spotlight
Thu 5:40 Implicit Regularization in Tensor Factorization
Noam Razin, Asaf Maman, Nadav Cohen
Spotlight
Thu 5:40 Directed Graph Embeddings in Pseudo-Riemannian Manifolds
Aaron Sim, Maciej Wiatrak, Angus Brayne, Páidí Creed, Saee Paliwal
Spotlight
Thu 5:40 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Spotlight
Thu 5:45 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Spotlight
Thu 5:45 Uniform Convergence, Adversarial Spheres and a Simple Remedy
Gregor Bachmann, Seyed Moosavi, Thomas Hofmann
Spotlight
Thu 5:45 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
Oral
Thu 6:00 Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
Andrew Ross, Finale Doshi-Velez
Spotlight
Thu 6:20 Whitening for Self-Supervised Representation Learning
Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto, Nicu Sebe
Spotlight
Thu 6:25 Nondeterminism and Instability in Neural Network Optimization
Cecilia Summers, Michael J Dinneen
Spotlight
Thu 6:25 Learning to Rehearse in Long Sequence Memorization
Zhu Zhang, Chang Zhou, Jianxin Ma, Zhijie Lin, Jingren Zhou, Hongxia Yang, Zhou Zhao
Spotlight
Thu 6:25 Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification
Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama
Spotlight
Thu 6:30 Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach
Federico Lopez, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard
Spotlight
Thu 6:30 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Spotlight
Thu 6:35 Robust Representation Learning via Perceptual Similarity Metrics
Saeid A Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal
Spotlight
Thu 6:35 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
Spotlight
Thu 6:35 Linear Transformers Are Secretly Fast Weight Programmers
Imanol Schlag, Kazuki Irie, Jürgen Schmidhuber
Spotlight
Thu 6:40 Conservative Objective Models for Effective Offline Model-Based Optimization
Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine
Spotlight
Thu 6:40 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Spotlight
Thu 6:40 Efficient Training of Robust Decision Trees Against Adversarial Examples
Daniël Vos, Sicco Verwer
Spotlight
Thu 6:40 Differentially Private Correlation Clustering
Mark Bun, Marek Elias, Janardhan Kulkarni
Spotlight
Thu 6:45 Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
Oral
Thu 7:00 CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang, Li Yinli, Cong Wang, Chao Shen, Qi Li
Oral
Thu 7:00 Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates
Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Guha Thakurta, Li Zhang
Oral
Thu 7:00 On Disentangled Representations Learned from Correlated Data
Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
Spotlight
Thu 7:20 Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Douze Matthijs, Francisco Massa, Alexandre Sablayrolles, Herve Jegou
Spotlight
Thu 7:20 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
Spotlight
Thu 7:20 Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
Spotlight
Thu 7:20 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Spotlight
Thu 7:25 SketchEmbedNet: Learning Novel Concepts by Imitating Drawings
Alexander Wang, Mengye Ren, Richard Zemel
Spotlight
Thu 7:30 GeomCA: Geometric Evaluation of Data Representations
Petra Poklukar, Anastasiia Varava, Danica Kragic
Spotlight
Thu 7:40 PHEW : Constructing Sparse Networks that Learn Fast and Generalize Well without Training Data
Shreyas Malakarjun Patil, Constantine Dovrolis
Spotlight
Thu 7:40 Environment Inference for Invariant Learning
Elliot Creager, Jörn Jacobsen, Richard Zemel
Spotlight
Thu 7:45 On the difficulty of unbiased alpha divergence minimization
Tomas Geffner, Justin Domke
Spotlight
Thu 7:45 Learning Binary Decision Trees by Argmin Differentiation
Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
Poster
Thu 9:00 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
Poster
Thu 9:00 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Poster
Thu 9:00 Whitening for Self-Supervised Representation Learning
Aleksandr Ermolov, Aliaksandr Siarohin, Enver Sangineto, Nicu Sebe
Poster
Thu 9:00 Efficient Training of Robust Decision Trees Against Adversarial Examples
Daniël Vos, Sicco Verwer
Poster
Thu 9:00 On the difficulty of unbiased alpha divergence minimization
Tomas Geffner, Justin Domke
Poster
Thu 9:00 Robust Representation Learning via Perceptual Similarity Metrics
Saeid A Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal
Poster
Thu 9:00 Differentially Private Correlation Clustering
Mark Bun, Marek Elias, Janardhan Kulkarni
Poster
Thu 9:00 Decoupling Representation Learning from Reinforcement Learning
Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
Poster
Thu 9:00 Private Alternating Least Squares: Practical Private Matrix Completion with Tighter Rates
Steve Chien, Prateek Jain, Walid Krichene, Steffen Rendle, Shuang Song, Abhradeep Guha Thakurta, Li Zhang
Poster
Thu 9:00 Hierarchical Clustering of Data Streams: Scalable Algorithms and Approximation Guarantees
Anand Rajagopalan, Fabio Vitale, Danny Vainstein, Gui Citovsky, Cecilia Procopiuc, Claudio Gentile
Poster
Thu 9:00 On Linear Identifiability of Learned Representations
Geoffrey Roeder, Luke Metz, Durk Kingma
Poster
Thu 9:00 Directed Graph Embeddings in Pseudo-Riemannian Manifolds
Aaron Sim, Maciej Wiatrak, Angus Brayne, Páidí Creed, Saee Paliwal
Poster
Thu 9:00 Nonmyopic Multifidelity Acitve Search
Quan Nguyen, Arghavan Modiri, Roman Garnett
Poster
Thu 9:00 Implicit Bias of Linear RNNs
Melika Emami, Moji Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson Fletcher
Poster
Thu 9:00 PHEW : Constructing Sparse Networks that Learn Fast and Generalize Well without Training Data
Shreyas Malakarjun Patil, Constantine Dovrolis
Poster
Thu 9:00 Binary Classification from Multiple Unlabeled Datasets via Surrogate Set Classification
Nan Lu, Shida Lei, Gang Niu, Issei Sato, Masashi Sugiyama
Poster
Thu 9:00 SketchEmbedNet: Learning Novel Concepts by Imitating Drawings
Alexander Wang, Mengye Ren, Richard Zemel
Poster
Thu 9:00 Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach
Federico Lopez, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard
Poster
Thu 9:00 CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang, Li Yinli, Cong Wang, Chao Shen, Qi Li
Poster
Thu 9:00 GeomCA: Geometric Evaluation of Data Representations
Petra Poklukar, Anastasiia Varava, Danica Kragic
Poster
Thu 9:00 Analyzing the tree-layer structure of Deep Forests
Ludovic Arnould, Claire Boyer, Erwan Scornet
Poster
Thu 9:00 Learning disentangled representations via product manifold projection
Marco Fumero, Luca Cosmo, Simone Melzi, Emanuele Rodola
Poster
Thu 9:00 Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer
Seungwon Lee, Sima Behpour, Eric Eaton
Poster
Thu 9:00 PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
Chaoyang He, Shen Li, Mahdi Soltanolkotabi, Salman Avestimehr
Poster
Thu 9:00 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
Poster
Thu 9:00 Linear Transformers Are Secretly Fast Weight Programmers
Imanol Schlag, Kazuki Irie, Jürgen Schmidhuber
Poster
Thu 9:00 Environment Inference for Invariant Learning
Elliot Creager, Jörn Jacobsen, Richard Zemel
Poster
Thu 9:00 Tilting the playing field: Dynamical loss functions for machine learning
Miguel Ruiz Garcia, Ge Zhang, Samuel Schoenholz, Andrea Liu
Poster
Thu 9:00 Learning to Rehearse in Long Sequence Memorization
Zhu Zhang, Chang Zhou, Jianxin Ma, Zhijie Lin, Jingren Zhou, Hongxia Yang, Zhou Zhao
Poster
Thu 9:00 Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, Tom Duerig
Poster
Thu 9:00 Conservative Objective Models for Effective Offline Model-Based Optimization
Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine
Poster
Thu 9:00 On Disentangled Representations Learned from Correlated Data
Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer
Poster
Thu 9:00 A Collective Learning Framework to Boost GNN Expressiveness for Node Classification
Mengyue Hang, Jennifer Neville, Bruno Ribeiro
Poster
Thu 9:00 Adapting to Delays and Data in Adversarial Multi-Armed Bandits
András György, Pooria Joulani
Poster
Thu 9:00 Phase Transitions, Distance Functions, and Implicit Neural Representations
Yaron Lipman
Poster
Thu 9:00 Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
Andrew Ross, Finale Doshi-Velez
Poster
Thu 9:00 Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
Poster
Thu 9:00 Coded-InvNet for Resilient Prediction Serving Systems
Tuan Dinh, Kangwook Lee
Poster
Thu 9:00 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Poster
Thu 9:00 Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Douze Matthijs, Francisco Massa, Alexandre Sablayrolles, Herve Jegou
Poster
Thu 9:00 Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels
Eran Malach, Pritish Kamath, Emmanuel Abbe, Nati Srebro
Poster
Thu 9:00 Implicit Regularization in Tensor Factorization
Noam Razin, Asaf Maman, Nadav Cohen
Poster
Thu 9:00 Learning Binary Decision Trees by Argmin Differentiation
Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
Poster
Thu 9:00 Uniform Convergence, Adversarial Spheres and a Simple Remedy
Gregor Bachmann, Seyed Moosavi, Thomas Hofmann
Poster
Thu 9:00 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Poster
Thu 9:00 GRAND: Graph Neural Diffusion
Ben Chamberlain, James Rowbottom, Maria Gorinova, Michael Bronstein, Stefan Webb, Emanuele Rossi
Poster
Thu 9:00 Nondeterminism and Instability in Neural Network Optimization
Cecilia Summers, Michael J Dinneen
Poster
Thu 9:00 Bayesian Attention Belief Networks
Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
Oral
Thu 17:00 Commutative Lie Group VAE for Disentanglement Learning
Xinqi Zhu, Chang Xu, Dacheng Tao
Oral
Thu 17:00 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang
Spotlight
Thu 17:20 Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks
Yukun Yang, Wenrui Zhang, Peng Li
Spotlight
Thu 17:20 Self-supervised Graph-level Representation Learning with Local and Global Structure
Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang
Spotlight
Thu 17:25 Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Chiang, Vyas Sekar
Spotlight
Thu 17:25 Generalization Error Bound for Hyperbolic Ordinal Embedding
Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza
Spotlight
Thu 17:25 Automatic variational inference with cascading flows
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
Spotlight
Thu 17:30 Exploiting Shared Representations for Personalized Federated Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
Spotlight
Thu 17:30 Neighborhood Contrastive Learning Applied to Online Patient Monitoring
Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch
Spotlight
Thu 17:30 Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models
José Lezama, Wei Chen, Qiang Qiu
Spotlight
Thu 17:30 MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie Laturnus, Philipp Berens
Spotlight
Thu 17:35 Simple and Effective VAE Training with Calibrated Decoders
Oleg Rybkin, Kostas Daniilidis, Sergey Levine
Spotlight
Thu 17:40 Robust Learning for Data Poisoning Attacks
Yunjuan Wang, Poorya Mianjy, Raman Arora
Spotlight
Thu 17:40 STRODE: Stochastic Boundary Ordinary Differential Equation
Huang Hengguan, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
Spotlight
Thu 17:45 Structured World Belief for Reinforcement Learning in POMDP
Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn
Oral
Thu 18:00 Dimensionality Reduction for the Sum-of-Distances Metric
Zhili Feng, Praneeth Kacham, David Woodruff
Oral
Thu 18:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Oral
Thu 18:00 Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Spotlight
Thu 18:20 Large Scale Private Learning via Low-rank Reparametrization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
Spotlight
Thu 18:20 Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
Spotlight
Thu 18:25 Watermarking Deep Neural Networks with Greedy Residuals
Hanwen Liu, Zhenyu Weng, Yuesheng Zhu
Spotlight
Thu 18:25 Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig
Spotlight
Thu 18:30 Unsupervised Part Representation by Flow Capsules
Sara Sabour Rouh Aghdam, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey Hinton, David Fleet
Spotlight
Thu 18:35 Active Slices for Sliced Stein Discrepancy
Wenbo Gong, Kaibo Zhang, Yingzhen Li, Jose Miguel Hernandez-Lobato
Spotlight
Thu 18:40 Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations
Patrick Emami, Pan He, Sanjay Ranka, Anand Rangarajan
Spotlight
Thu 18:40 When Does Data Augmentation Help With Membership Inference Attacks?
Yigitcan Kaya, Tudor Dumitras
Spotlight
Thu 18:45 Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
Spotlight
Thu 18:45 Temporal Predictive Coding For Model-Based Planning In Latent Space
Tung Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon
Oral
Thu 19:00 Graph Neural Networks Inspired by Classical Iterative Algorithms
Yang Yongyi, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
Spotlight
Thu 19:15 Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
Guangyu Shen, Yingqi Liu, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng, Shiqing Ma, Xiangyu Zhang
Spotlight
Thu 19:20 FILTRA: Rethinking Steerable CNN by Filter Transform
Bo Li, Qili Wang, Gim Hee Lee
Spotlight
Thu 19:25 Link Prediction with Persistent Homology: An Interactive View
Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen
Spotlight
Thu 19:30 Conjugate Energy-Based Models
Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent
Spotlight
Thu 19:35 Sharper Generalization Bounds for Clustering
Shaojie Li, Yong Liu
Spotlight
Thu 19:35 Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
Kieran Murphy, Carlos Esteves, Varun Jampani, Srikumar Ramalingam, Ameesh Makadia
Spotlight
Thu 19:40 Equivariant Networks for Pixelized Spheres
Mehran Shakerinava, Siamak Ravanbakhsh
Spotlight
Thu 19:40 Streaming and Distributed Algorithms for Robust Column Subset Selection
Shuli Jiang, Dongyu Li, Irene Mengze Li, Arvind Mahankali, David Woodruff
Spotlight
Thu 19:45 Efficient Statistical Tests: A Neural Tangent Kernel Approach
Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba
Spotlight
Thu 20:30 Conditional Temporal Neural Processes with Covariance Loss
Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi
Spotlight Session
Thu 20:30 Deep Learning 3
Spotlight
Thu 20:30 Discretization Drift in Two-Player Games
Mihaela Rosca, Yan Wu, Benoit Dherin, David GT Barrett
Spotlight
Thu 20:35 Budgeted Heterogeneous Treatment Effect Estimation
Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou
Spotlight
Thu 20:35 Elementary superexpressive activations
Dmitry Yarotsky
Spotlight
Thu 20:40 ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi
Spotlight
Thu 20:40 A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance
Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona
Spotlight
Thu 20:45 Overcoming Catastrophic Forgetting by Bayesian Generative Regularization
Patrick Chen Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
Spotlight
Thu 20:45 Diffusion Earth Mover's Distance and Distribution Embeddings
Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid Macdonald, MANIK KUCHROO, Ronald Coifman, Guy Wolf, Smita Krishnaswamy
Spotlight
Thu 20:50 CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
Hanshu YAN, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Tan, Masashi Sugiyama
Spotlight
Thu 20:50 Locally Adaptive Label Smoothing Improves Predictive Churn
Dara Bahri, Heinrich Jiang
Spotlight
Thu 20:50 GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya
Poster
Thu 21:00 ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks
Jungmin Kwon, Jeongseop Kim, Hyunseo Park, In Kwon Choi
Poster
Thu 21:00 When Does Data Augmentation Help With Membership Inference Attacks?
Yigitcan Kaya, Tudor Dumitras
Poster
Thu 21:00 Which transformer architecture fits my data? A vocabulary bottleneck in self-attention
Noam Wies, Yoav Levine, Daniel Jannai, Amnon Shashua
Poster
Thu 21:00 Structured World Belief for Reinforcement Learning in POMDP
Gautam Singh, Skand Peri, Junghyun Kim, Hyunseok Kim, Sungjin Ahn
Poster
Thu 21:00 Sharper Generalization Bounds for Clustering
Shaojie Li, Yong Liu
Poster
Thu 21:00 Conjugate Energy-Based Models
Hao Wu, Babak Esmaeili, Michael Wick, Jean-Baptiste Tristan, Jan-Willem van de Meent
Poster
Thu 21:00 Unsupervised Part Representation by Flow Capsules
Sara Sabour Rouh Aghdam, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey Hinton, David Fleet
Poster
Thu 21:00 A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance
Xiaoyu Li, Zhenxun Zhuang, Francesco Orabona
Poster
Thu 21:00 Watermarking Deep Neural Networks with Greedy Residuals
Hanwen Liu, Zhenyu Weng, Yuesheng Zhu
Poster
Thu 21:00 Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
Guangyu Shen, Yingqi Liu, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng, Shiqing Ma, Xiangyu Zhang
Poster
Thu 21:00 Automatic variational inference with cascading flows
Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
Poster
Thu 21:00 Locally Adaptive Label Smoothing Improves Predictive Churn
Dara Bahri, Heinrich Jiang
Poster
Thu 21:00 Link Prediction with Persistent Homology: An Interactive View
Zuoyu Yan, Tengfei Ma, Liangcai Gao, Zhi Tang, Chao Chen
Poster
Thu 21:00 CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
Hanshu YAN, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Tan, Masashi Sugiyama
Poster
Thu 21:00 Generalization Error Bound for Hyperbolic Ordinal Embedding
Atsushi Suzuki, Atsushi Nitanda, Jing Wang, Linchuan Xu, Kenji Yamanishi, Marc Cavazza
Poster
Thu 21:00 Temporal Predictive Coding For Model-Based Planning In Latent Space
Tung Nguyen, Rui Shu, Tuan Pham, Hung Bui, Stefano Ermon
Poster
Thu 21:00 Efficient Iterative Amortized Inference for Learning Symmetric and Disentangled Multi-Object Representations
Patrick Emami, Pan He, Sanjay Ranka, Anand Rangarajan
Poster
Thu 21:00 Robust Learning for Data Poisoning Attacks
Yunjuan Wang, Poorya Mianjy, Raman Arora
Poster
Thu 21:00 Graph Neural Networks Inspired by Classical Iterative Algorithms
Yang Yongyi, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
Poster
Thu 21:00 Neighborhood Contrastive Learning Applied to Online Patient Monitoring
Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch
Poster
Thu 21:00 Self-supervised Graph-level Representation Learning with Local and Global Structure
Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang
Poster
Thu 21:00 Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Chiang, Vyas Sekar
Poster
Thu 21:00 Dimensionality Reduction for the Sum-of-Distances Metric
Zhili Feng, Praneeth Kacham, David Woodruff
Poster
Thu 21:00 Demystifying Inductive Biases for (Beta-)VAE Based Architectures
Dominik Zietlow, Michal Rolinek, Georg Martius
Poster
Thu 21:00 Exploiting Shared Representations for Personalized Federated Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
Poster
Thu 21:00 Run-Sort-ReRun: Escaping Batch Size Limitations in Sliced Wasserstein Generative Models
José Lezama, Wei Chen, Qiang Qiu
Poster
Thu 21:00 Overcoming Catastrophic Forgetting by Bayesian Generative Regularization
Patrick Chen Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
Poster
Thu 21:00 FILTRA: Rethinking Steerable CNN by Filter Transform
Bo Li, Qili Wang, Gim Hee Lee
Poster
Thu 21:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Poster
Thu 21:00 Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou, Xuezhe Ma, Paul Michel, Graham Neubig
Poster
Thu 21:00 GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
Idan Achituve, Aviv Navon, Yochai Yemini, Gal Chechik, Ethan Fetaya
Poster
Thu 21:00 Budgeted Heterogeneous Treatment Effect Estimation
Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou
Poster
Thu 21:00 MorphVAE: Generating Neural Morphologies from 3D-Walks using a Variational Autoencoder with Spherical Latent Space
Sophie Laturnus, Philipp Berens
Poster
Thu 21:00 Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks
Yukun Yang, Wenrui Zhang, Peng Li
Poster
Thu 21:00 Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Mingkang Zhu, Tianlong Chen, Zhangyang Wang
Poster
Thu 21:00 Private Stochastic Convex Optimization: Optimal Rates in L1 Geometry
Hilal Asi, Vitaly Feldman, Tomer Koren, Kunal Talwar
Poster
Thu 21:00 Discretization Drift in Two-Player Games
Mihaela Rosca, Yan Wu, Benoit Dherin, David GT Barrett
Poster
Thu 21:00 Streaming and Distributed Algorithms for Robust Column Subset Selection
Shuli Jiang, Dongyu Li, Irene Mengze Li, Arvind Mahankali, David Woodruff
Poster
Thu 21:00 Equivariant Networks for Pixelized Spheres
Mehran Shakerinava, Siamak Ravanbakhsh
Poster
Thu 21:00 Elementary superexpressive activations
Dmitry Yarotsky
Poster
Thu 21:00 Large Scale Private Learning via Low-rank Reparametrization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
Poster
Thu 21:00 Efficient Statistical Tests: A Neural Tangent Kernel Approach
Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba
Poster
Thu 21:00 Conditional Temporal Neural Processes with Covariance Loss
Boseon Yoo, Jiwoo Lee, Janghoon Ju, Seijun Chung, Soyeon Kim, Jaesik Choi
Poster
Thu 21:00 Diffusion Earth Mover's Distance and Distribution Embeddings
Alexander Tong, Guillaume Huguet, Amine Natik, Kincaid Macdonald, MANIK KUCHROO, Ronald Coifman, Guy Wolf, Smita Krishnaswamy
Poster
Thu 21:00 Simple and Effective VAE Training with Calibrated Decoders
Oleg Rybkin, Kostas Daniilidis, Sergey Levine
Poster
Thu 21:00 Commutative Lie Group VAE for Disentanglement Learning
Xinqi Zhu, Chang Xu, Dacheng Tao
Poster
Thu 21:00 Active Slices for Sliced Stein Discrepancy
Wenbo Gong, Kaibo Zhang, Yingzhen Li, Jose Miguel Hernandez-Lobato
Poster
Thu 21:00 Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
Kieran Murphy, Carlos Esteves, Varun Jampani, Srikumar Ramalingam, Ameesh Makadia
Poster
Thu 21:00 STRODE: Stochastic Boundary Ordinary Differential Equation
Huang Hengguan, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
Workshop
Fri 5:55 ICML Workshop on Representation Learning for Finance and E-Commerce Applications
Senthil Kumar, Sameena Shah, Joan Bruna, Tom Goldstein, Erik Mueller, Oleg Rokhlenko, Hongxia Yang, Jianpeng Xu, Oluwatobi O Olabiyi, Charese Smiley, Bayan Bruss, Saurabh H Nagrecha, Svitlana Vyetrenko
Workshop
Fri 6:00 Invited Talk 1: Geometric Deep Learning: Grids, Graphs, Groups, Gauges
Michael Bronstein
Workshop
Fri 6:00 Uncertainty and Robustness in Deep Learning
Balaji Lakshminarayanan, Dan Hendrycks, Sharon Li, Jasper Snoek, Silvia Chiappa, Sebastian Nowozin, Tom Dietterich
Workshop
Fri 6:30 Invited Talk 2: Addressing Model Bias and Uncertainty via Evidential Deep Learning
Daniela Rus
Workshop
Fri 7:30 Dynamic Pruning of a Neural Network via Gradient Signal-to-Noise Ratio
Julien Siems
Workshop
Fri 7:36 Mutation is all you need
Lennart Schneider
Workshop
Fri 8:15 Some Thoughts on Generalization, Robustness, and their application with CLIP
Alec Radford
Workshop
Fri 9:52 Tabular Data: Deep Learning is Not All You Need
Ravid Shwartz-Ziv
Workshop
Fri 9:53 Automated Learning Rate Scheduler for Large-batch Training
Chiheon Kim
Workshop
Fri 11:00 Invited Talk 8: Deep Learning on Graphs for Natural Language Processing
Lingfei Wu
Workshop
Fri 11:00 Automating deep learning to interpret human genomic variations
Olga Troyanskaya
Workshop
Fri 12:30 Evaluating deep learning models with applications to NLP
Nazneen Rajani
Workshop
Fri 13:00 Enhancing Laboratory-scale Flow Imaging of Fractured Geological Media with Deep Learning Super Resolution
Manju Pharkavi Murugesu
Workshop
Fri 13:31 Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
Gyri Reiersen
Workshop
Sat 6:00 Jun Zhu. Understand and Benchmark Adversarial Robustness of Deep Learning
Chaowei Xiao
Workshop
Sat 7:00 Information-Theoretic Methods for Rigorous, Responsible, and Reliable Machine Learning (ITR3)
Ahmad Beirami, Flavio Calmon, Berivan Isik, Haewon Jeong, Matthew Nokleby, Cynthia Rush
Workshop
Sat 7:20 Pin-Yu Chen. Adversarial Machine Learning for Good
Workshop
Sat 7:30 Data Summarization via Bilevel Coresets
Andreas Krause
Workshop
Sat 8:05 Conjugate gradient techniques for nonconvex optimization
Clément Royer
Workshop
Sat 10:00 The Polyak-Lojasiewicz condition as a framework for over-parameterized optimization and its application to deep learning
Mikhail Belkin
Workshop
Sat 11:45 Morning Poster Session: Electric Load Forecasting with Boosting based Sample Transfer
Tracy Cui
Workshop
Sat 11:45 Morning Poster Session: Changepoint Detection using Self Supervised Variational AutoEncoders
Sourav Chatterjee
Workshop
Sat 12:04 Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization
Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
Workshop
Sat 12:09 SVP-CF: Selection via Proxy for Collaborative Filtering Data
Noveen Sachdeva, Julian McAuley, Carole-Jean Wu
Workshop
Sat 13:07 Mitigating Memorization in Sample Selection for Learning with Noisy Labels
Kyeongbo Kong, Junggi Lee, Youngchul Kwak, Young-Rae Cho, Seong-Eun Kim, Woo-jin Song
Workshop
Sat 13:30 Contributed Talk #9
Keji Han
Workshop
Sat 14:20 Towards understanding how momentum improves generalization in deep learning
Samy Jelassi, Yuanzhi Li
Workshop
Sat 14:30 Computationally Efficient Data Selection for Deep Learning
Cody Coleman
Workshop
Sat 14:50 A Universal Law of Robustness via Isoperimetry
Sebastien Bubeck, Mark Sellke
Workshop
Sat 14:50 Computationally Efficient Data Selection for Deep Learning Live Q&A
Workshop
Sat 15:20 Core-set Sampling for Efficient Neural Architecture Search
Jae-hun Shim, Kyeongbo Kong, Suk-Ju Kang
Workshop
Sat 16:09 Effective Evaluation of Deep Active Learning on Image Classification Tasks
Nathan Beck, Durga S, Ganesh Ramakrishnan, Rishabh Lyer
Workshop
Sat 16:15 Empirical Frequentist Coverage of Deep Learning Uncertainty Quantification Procedures (Spotlight #6)
Ben Kompa
Workshop
Core-set Sampling for Efficient Neural Architecture Search
Jae-hun Shim, Kyeongbo Kong, Suk-Ju Kang
Workshop
Mitigating Memorization in Sample Selection for Learning with Noisy Labels
Kyeongbo Kong, Junggi Lee, Youngchul Kwak, Young-Rae Cho, Seong-Eun Kim, Woo-jin Song
Workshop
SVP-CF: Selection via Proxy for Collaborative Filtering Data
Noveen Sachdeva, Julian McAuley, Carole-Jean Wu
Workshop
Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization
Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
Workshop
A Data Subset Selection Framework for Efficient Hyper-Parameter Tuning and Automatic Machine Learning
Savan Amitbhai Visalpara, Krishnateja Killamsetty, Rishabh Lyer
Workshop
Geometrical Homogeneous Clustering for Image Data Reduction
Shril Mody, Janvi Thakkar, Devvrat Joshi, Siddharth Soni, Nipun Batra, Rohan Patil
Workshop
Deep Learning with Quantified Uncertainty for Free Electron Laser Scientific Facilities
Workshop
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data
Workshop
MetaDataset: A Dataset of Datasets for Evaluating Distribution Shifts and Training Conflicts
Weixin Liang, James Zou, Weixin Liang
Workshop
Towards Principled Disentanglement for Domain Generalization
Hanlin Zhang, Yi-Fan Zhang, Weiyang Liu, Adrian Weller, Bernhard Schölkopf, Eric Xing
Workshop
An Efficient DP-SGD Mechanism for Large Scale NLP Models
Christophe Dupuy, Radhika Arava, Rahul Gupta, Anna Rumshisky
Workshop
DP-SGD vs PATE: Which Has Less Disparate Impact on Model Accuracy?
Archit Uniyal, Rakshit Naidu, Sasikanth Kotti, Patrik Joslin Kenfack, Sahib Singh, FatemehSadat Mireshghallah
Workshop
Out-of-Distribution Robustness in Deep Learning Compression
Eric Lei, Hamed Hassani
Workshop
Differentially Private Bayesian Neural Network
Woody Bu, Qiyiwen Zhang, Kan Chen, Qi Long
Workshop
On the Convergence of Deep Learning with Differential Privacy
Woody Bu, Hua Wang, Qi Long, Weijie Su
Workshop
Improving Privacy-Preserving Deep Learning With Immediate Sensitivity
Tim Stevens, David Darais, Ben U Gelman, David Slater, Joseph Near
Workshop
Differentially private training of neural networks with Langevin dynamics for calibrated predictive uncertainty
Moritz Knolle, Alexander Ziller, Dmitrii Usynin, Rickmer Braren, Marcus Makowski, Daniel Rueckert, Georgios Kaissis
Workshop
Tabular Data: Deep Learning is Not All You Need
Ravid Shwartz-Ziv, Amitai Armon
Workshop
Automated Learning Rate Scheduler for Large-batch Training
Chiheon Kim, Saehoon Kim, Jongmin Kim, Donghoon Lee, SUNGWOONG KIM
Workshop
Mutation is all you need
Lennart Schneider, Florian Pfisterer, Martin Binder, Bernd Bischl
Workshop
Dynamic Pruning of a Neural Network via Gradient Signal-to-Noise Ratio
Julien N Siems, Aaron Klein, Cedric Archambeau, Maren Mahsereci
Workshop
MACDA: Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction
Tri Nguyen, Thomas Quinn, Thin Nguyen, Truyen Tran
Workshop
Tree-based local explanations of machine learning model predictions – AraucanaXAI
Enea Parimbelli, Giovanna Nicora, Szymon Wilk, Wojtek Michalowski, Riccardo Bellazzi
Workshop
Enhancing interpretability and reducing uncertainties in deep learning of electrocardiograms using a sub-waveform representation
Hossein Honarvar, Chirag Agarwal, Sulaiman Somani, Girish Nadkarni, Marinka Zitnik, Fei Wang, Benjamin Glicksberg
Workshop
Towards Privacy-preserving Explanations in Medical Image Analysis
Helena Montenegro, Wilson Silva, Jaime S. Cardoso
Workshop
Do You See What I See? A Comparison of Radiologist Eye Gaze to Computer Vision Saliency Maps for Chest X-ray Classification
Jesse Kim, Helen Zhou, Zachary Lipton
Workshop
Variable selection via the sum of single effect neural networks with credible sets
Wei Cheng, Sohini Ramachandran, Lorin Crawford
Workshop
Improving Adversarial Robustness in 3D Point Cloud Classification via Self-Supervisions
Jiachen Sun, yulong cao, Christopher Choy, Zhiding Yu, Chaowei Xiao, Anima Anandkumar, Zhuoqing Morley Mao
Workshop
Auditing AI models for Verified Deployment under Semantic Specifications
Homanga Bharadhwaj, De-An Huang, Chaowei Xiao, Anima Anandkumar, Animesh Garg
Workshop
Delving into the Remote Adversarial Patch in Semantic Segmentation
yulong cao, Jiachen Sun, Chaowei Xiao, Qi Alfred Chen, Zhuoqing Morley Mao
Workshop
Pretrained Encoders are All You Need
Mina Khan, Advait Rane, Srivatsa P, Shriram Chenniappa, Rishabh Anand, Sherjil Ozair, Patricia Maes
Workshop
Prediction of RNA-protein Interactions Using a Nucleotide Language Model
Keisuke Yamada
Workshop
Synthetic COVID-19 Chest X-ray Dataset for Computer-Aided Diagnosis
Hasib Zunair
Workshop
Deep neural networks identify sequence context features predictive of transcription factor binding
AN ZHENG
Workshop
Representation of Features as Images with Neighborhood Dependencies forCompatibility with Convolutional Neural Networks
Omid Bazgir
Workshop
pmVAE: Learning Interpretable Single-Cell Representations with Pathway Modules
Stefan Stark
Workshop
Variable selection via the sum of single effect neural networks with credible sets
Wei Cheng, Sohini Ramachandran, Lorin Crawford
Workshop
VICAUSE: Simultaneous missing value imputation and causal discovery
Pablo Morales-Alvarez, Angus Lamb, Simon Woodhead, Simon Pyton Jones, Miltiadis Allamanis, Cheng Zhang
Workshop
A Survey on Deep Learning of Potential Outcomes From a Social Science Perspective
Bernard Koch, Niki Kilbertus
Workshop
A Universal Law of Robustness via Isoperimetry
Sebastien Bubeck, Mark Sellke
Workshop
Towards understanding how momentum improves generalization in deep learning
Samy Jelassi, Yuanzhi Li
Workshop
PreferenceNet: Encoding Human Preferences in Auction Design
Neehar Peri, Michael Curry, Samuel Dooley, John P Dickerson
Workshop
High Frequency EEG Artifact Detection with Uncertainty via Early Exit Paradigm
Lorena Qendro, Alex Campbell, Pietro Lió, Cecilia Mascolo
Workshop
Active Learning under Pool Set Distribution Shift and Noisy Data
Andreas Kirsch, Tom Rainforth, Yarin Gal
Workshop
On The State of Data In Computer Vision: Human Annotations Remain Indispensable for Developing Deep Learning Models.
Zeyad Emam, Sasha Harrison, Felix Lau, Aerin Kim
Workshop
DFUQ poster 2 -- An Approximate Parallel Tempering for Uncertainty Quantification in Deep Learning
Workshop
Poster: Enhancing Laboratory-scale Flow Imaging of Fractured Geological Media with Deep Learning Super Resolution
Workshop
Poster: Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery
Workshop
DFUQ poster 2 -- Locally Valid and Discriminative Confidence Intervals for Deep Learning Models
Workshop
DFUQ poster 2 -- Interval Deep Learning
Workshop
Adversarial Interaction Attacks: Fooling AI to Misinterpret Human Intentions
Nodens Koren, Xingjun Ma, Qiuhong Ke, Yisen Wang, James Bailey
Workshop
Non-Robust Feature Mapping in Deep Reinforcement Learning
Ezgi Korkmaz
Workshop
Long-term Cross Adversarial Training: A Robust Meta-learning Method for Few-shot Classification Tasks
FAN LIU, Shuyu Zhao, Xuelong Dai, Bin Xiao
Workshop
Membership Inference Attacks on Lottery Ticket Networks
Aadesh Bagmar, Shishira Maiya, Shruti Bidwalkar, Amol Deshpande
Workshop
Disrupting Model Training with Adversarial Shortcuts
Aditya Kusupati, Tadayoshi Kohno, Ivan Evtimov, Ian Covert
Workshop
Is It Time to Redefine the Classification Task for Deep Learning Systems?
Keji Han, Yun Li, Songcan Chen
Workshop
Out of Distribution Detection and Adversarial Attacks on Deep Neural Networks for Robust Medical Image Analysis
Anisie Uwimana, Ransalu Senanayake
Workshop
Adversarial EXEmples: Functionality-preserving Optimization of Adversarial Windows Malware
Luca Demetrio, Battista Biggio, Giovanni Lagorio, Alessandro Armando, Fabio Roli, Luca Demetrio
Workshop
Adversarial Semantic Contour for Object Detection
Yichi Zhang, Zijian Zhu, Xiao Yang, Jun Zhu
Workshop
Poisoning the Search Space in Neural Architecture Search
Robert Wu, Nayan Saxena, Rohan Jain
Workshop
Defending Adversaries Using Unsupervised Feature Clustering VAE
Cheng Zhang, Pan Gao
Workshop
Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations
Ziquan Liu, Yufei Cui, Antoni Chan
Workshop
Robust Recovery of Adversarial Samples
Tejas Bana, Siddhant Kulkarni, Jatan Loya
Workshop
DeepPolicyTracker: Tracking Changes In Environmental Policy In The Brazilian Federal Official Gazette With Deep Learning
Flávio Cação
Workshop
Long-term Burned Area Reconstruction through Deep Learning
Seppe Lampe
Workshop
Strategic Instrumental Variable Regression: Recovering Causal Relationships From Strategic Responses
Keegan Harris, Daniel Ngo, Logan Stapleton, Hoda Heidari, Steven Wu
Workshop
Stateful Strategic Regression
Keegan Harris, Hoda Heidari, Steven Wu
Workshop
Commercial Vehicle Traffic Detection from Satellite Imagery with Deep Learning
Michael Mommert
Workshop
Deep learning applied to sea surface semantic segmentation: Filtering sunglint from aerial imagery
Teodor Vrecica
Workshop
On the interplay between data structure and loss function: an analytical study of generalization for classification
Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli
Workshop
Finite-Sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime
Niladri Chatterji, Phil Long
Workshop
How does Over-Parametrization Lead to Acceleration for Learning a Single Teacher Neuron with Quadratic Activation?
Jun-Kun Wang, Jake Abernethy
Workshop
Robust Generalization of Quadratic Neural Networks via Function Identification
Kan Xu, Hamsa Bastani, Osbert Bastani
Workshop
Epoch-Wise Double Descent: A Theory of Multi-scale Feature Learning Dynamics
Mohammad Pezeshki, Amartya Mitra, Yoshua Bengio, Guillaume Lajoie
Workshop
Deep Learning for Spatiotemporal Anomaly Forecasting: A Case Study of Marine Heatwaves
Ding Ning
Workshop
Deep learning network to project future Arctic ocean waves
Merce Casas Prat
Workshop
Examining the nexus of environmental policy, climate physics, and maritime shipping with deep learning models and space-borne data
Tianle Yuan
Workshop
Effective Evaluation of Deep Active Learning on Image Classification Tasks
Nathan Beck, Durga S, Ganesh Ramakrishnan, Rishabh Lyer