245 Results

Tutorial
Mon 1:00 Representation Learning Without Labels
S. M. Ali Eslami, Irina Higgins, Danilo J. Rezende
Poster
Tue 7:00 Laplacian Regularized Few-Shot Learning
Imtiaz Ziko, Jose Dolz, Eric Granger, Ismail Ben Ayed
Poster
Tue 7:00 Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting
Nic Dalmasso, Rafael Izbicki, Ann Lee
Poster
Tue 7:00 NGBoost: Natural Gradient Boosting for Probabilistic Prediction
Tony Duan, Anand Avati, Daisy Ding, Khanh K. Thai, Sanjay Basu, Andrew Ng, Alejandro Schuler
Poster
Tue 7:00 Generative Flows with Matrix Exponential
Changyi Xiao, Ligang Liu
Poster
Tue 7:00 Mutual Transfer Learning for Massive Data
Ching-Wei Cheng, Xingye Qiao, Guang Cheng
Poster
Tue 7:00 Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling
Will Grathwohl, Kuan-Chieh Wang, Jörn Jacobsen, David Duvenaud, Richard Zemel
Poster
Tue 7:00 Faster Graph Embeddings via Coarsening
Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang
Poster
Tue 7:00 All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference
Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan
Poster
Tue 7:00 Deep Reasoning Networks for Unsupervised Pattern De-mixing with Constraint Reasoning
Di Chen, Yiwei Bai, Wenting Zhao, Sebastian Ament, John Gregoire, Carla Gomes
Poster
Tue 7:00 Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms
Chaosheng Dong, Bo Zeng
Poster
Tue 7:00 Layered Sampling for Robust Optimization Problems
Hu Ding, Zixiu Wang
Poster
Tue 7:00 Improving Generative Imagination in Object-Centric World Models
Zhixuan Lin, Yi-Fu Wu, Skand Peri, Bofeng Fu, Jindong Jiang, Sungjin Ahn
Poster
Tue 7:00 Contrastive Multi-View Representation Learning on Graphs
Kaveh Hassani, Amir Hosein Khasahmadi
Poster
Tue 7:00 Efficient Domain Generalization via Common-Specific Low-Rank Decomposition
Vihari Piratla, Praneeth Netrapalli, Sunita Sarawagi
Poster
Tue 7:00 LTF: A Label Transformation Framework for Correcting Label Shift
Jiaxian Guo, Mingming Gong, Tongliang Liu, Kun Zhang, Dacheng Tao
Poster
Tue 7:00 Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
shuai zhang, Meng Wang, Sijia Liu, Pin-Yu Chen, Jinjun Xiong
Poster
Tue 7:00 Learning with Multiple Complementary Labels
LEI FENG, Takuo Kaneko, Bo Han, Gang Niu, Bo An, Masashi Sugiyama
Poster
Tue 7:00 Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data
Lan-Zhe Guo, Zhen-Yu Zhang, Yuan Jiang, Yufeng Li, Zhi-Hua Zhou
Poster
Tue 7:00 Minimax Rate for Learning From Pairwise Comparisons in the BTL Model
Julien Hendrickx, Alex Olshevsky, Venkatesh Saligrama
Poster
Tue 7:00 Individual Fairness for k-Clustering
Sepideh Mahabadi, Ali Vakilian
Poster
Tue 7:00 Searching to Exploit Memorization Effect in Learning with Noisy Labels
QUANMING YAO, Hansi Yang, Bo Han, Gang Niu, James Kwok
Poster
Tue 7:00 On the Global Optimality of Model-Agnostic Meta-Learning
Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
Poster
Tue 7:00 Training Binary Neural Networks through Learning with Noisy Supervision
Kai Han, Yunhe Wang, Yixing Xu, Chunjing Xu, Enhua Wu, Chang Xu
Poster
Tue 7:00 A Simple Framework for Contrastive Learning of Visual Representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, Geoffrey Hinton
Poster
Tue 7:00 Confidence-Aware Learning for Deep Neural Networks
Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang
Poster
Tue 7:00 Amortized Population Gibbs Samplers with Neural Sufficient Statistics
Hao Wu, Heiko Zimmermann, Eli Sennesh, Tuan Anh Le, Jan-Willem van de Meent
Poster
Tue 7:00 On Variational Learning of Controllable Representations for Text without Supervision
Peng Xu, Jackie Chi Kit Cheung, Yanshuai Cao
Poster
Tue 8:00 Parameterized Rate-Distortion Stochastic Encoder
Quan Hoang, Trung Le, Dinh Phung
Poster
Tue 8:00 Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
Yibo Jiang, Cengiz Pehlevan
Poster
Tue 8:00 Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM
Kunal Menda, Jean de Becdelievre, Jayesh Gupta, Ilan Kroo, Mykel Kochenderfer, Zachary Manchester
Poster
Tue 8:00 DROCC: Deep Robust One-Class Classification
Sachin Goyal, Aditi Raghunathan, Moksh Jain, Harsha Vardhan Simhadri, Prateek Jain
Poster
Tue 8:00 The Tree Ensemble Layer: Differentiability meets Conditional Computation
Hussein Hazimeh, Natalia Ponomareva, Petros Mol, Zhenyu Tan, Rahul Mazumder
Poster
Tue 8:00 Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures
Chiru Bhattacharyya, Ravindran Kannan
Poster
Tue 8:00 Meta-learning for Mixed Linear Regression
Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh
Poster
Tue 8:00 Oracle Efficient Private Non-Convex Optimization
Seth Neel, Aaron Roth, Giuseppe Vietri, Steven Wu
Poster
Tue 8:00 An end-to-end approach for the verification problem: learning the right distance
Joao Monteiro, Isabela Albuquerque, Jahangir Alam, R Devon Hjelm, Tiago Falk
Poster
Tue 9:00 Learning Compound Tasks without Task-specific Knowledge via Imitation and Self-supervised Learning
Sang-Hyun Lee, Seung-Woo Seo
Poster
Tue 9:00 Rank Aggregation from Pairwise Comparisons in the Presence of Adversarial Corruptions
Arpit Agarwal, Shivani Agarwal, Sanjeev Khanna, Prathamesh Patil
Poster
Tue 9:00 Obtaining Adjustable Regularization for Free via Iterate Averaging
Jingfeng Wu, Vladimir Braverman, Lin Yang
Poster
Tue 9:00 Recovery of Sparse Signals from a Mixture of Linear Samples
Soumyabrata Pal, Arya Mazumdar
Poster
Tue 9:00 Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles
Dylan Foster, Alexander Rakhlin
Poster
Tue 9:00 Deep k-NN for Noisy Labels
Dara Bahri, Heinrich Jiang, Maya Gupta
Poster
Tue 9:00 Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization
Sicheng Zhu, Xiao Zhang, David Evans
Poster
Tue 9:00 Learning Algebraic Multigrid Using Graph Neural Networks
Ilay Luz, Meirav Galun, Haggai Maron, Ronen Basri, Irad Yavneh
Poster
Tue 9:00 Certified Robustness to Label-Flipping Attacks via Randomized Smoothing
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar, Zico Kolter
Poster
Tue 9:00 Being Bayesian about Categorical Probability
Taejong Joo, Uijung Chung, Min-Gwan Seo
Poster
Tue 10:00 Federated Learning with Only Positive Labels
Felix Xinnan Yu, Ankit Singh Rawat, Aditya Menon, Sanjiv Kumar
Poster
Tue 10:00 Generative Pretraining From Pixels
Mark Chen, Alec Radford, Rewon Child, Jeffrey K Wu, Heewoo Jun, David Luan, Ilya Sutskever
Poster
Tue 10:00 Topological Autoencoders
Michael Moor, Max Horn, Bastian Rieck, Karsten Borgwardt
Poster
Tue 10:00 Structured Prediction with Partial Labelling through the Infimum Loss
Vivien Cabannnes, Alessandro Rudi, Francis Bach
Poster
Tue 10:00 Automatic Shortcut Removal for Self-Supervised Representation Learning
Matthias Minderer, Olivier Bachem, Neil Houlsby, Michael Tschannen
Poster
Tue 10:00 Explainable k-Means and k-Medians Clustering
Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost
Poster
Tue 11:00 Which Tasks Should Be Learned Together in Multi-task Learning?
Trevor Standley, Amir Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, Silvio Savarese
Poster
Tue 11:00 Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates
Yang Liu, Hongyi Guo
Poster
Tue 11:00 Understanding and Mitigating the Tradeoff between Robustness and Accuracy
Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, Percy Liang
Poster
Tue 11:00 Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu, Wenkai Xu, Jie Lu, Guangquan Zhang, Arthur Gretton, D.J. Sutherland
Poster
Tue 11:00 Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills
Victor Campos, Alexander Trott, Caiming Xiong, Richard Socher, Xavier Giro-i-Nieto, Jordi Torres
Poster
Tue 11:00 Smaller, more accurate regression forests using tree alternating optimization
Arman Zharmagambetov, Miguel Carreira-Perpinan
Poster
Tue 11:00 Quantum Expectation-Maximization for Gaussian mixture models
Alessandro Luongo, Iordanis Kerenidis, Anupam Prakash
Poster
Tue 11:00 Consistent Structured Prediction with Max-Min Margin Markov Networks
Alex Nowak, Francis Bach, Alessandro Rudi
Poster
Tue 12:00 IPBoost – Non-Convex Boosting via Integer Programming
Marc Pfetsch, Sebastian Pokutta
Poster
Tue 12:00 Partial Trace Regression and Low-Rank Kraus Decomposition
Hachem Kadri, Stephane Ayache, Riikka Huusari, alain rakotomamonjy, Ralaivola Liva
Poster
Tue 12:00 A distributional view on multi-objective policy optimization
Abbas Abdolmaleki, Sandy Huang, Leonard Hasenclever, Michael Neunert, Francis Song, Martina Zambelli, Murilo Martins, Nicolas Heess, Raia Hadsell, Martin Riedmiller
Poster
Tue 13:00 StochasticRank: Global Optimization of Scale-Free Discrete Functions
Aleksei Ustimenko, Liudmila Prokhorenkova
Poster
Tue 13:00 Predictive Sampling with Forecasting Autoregressive Models
Auke Wiggers, Emiel Hoogeboom
Poster
Tue 13:00 The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture
Francesca Mignacco, Florent Krzakala, Yue Lu, Pierfrancesco Urbani, Lenka Zdeborova
Poster
Tue 13:00 Uncertainty Estimation Using a Single Deep Deterministic Neural Network
Joost van Amersfoort, Lewis Smith, Yee-Whye Teh, Yarin Gal
Poster
Tue 13:00 Supervised learning: no loss no cry
Richard Nock, Aditya Menon
Poster
Tue 13:00 Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities
Jonas Köhler, Leon Klein, Frank Noe
Poster
Tue 13:00 Near-Tight Margin-Based Generalization Bounds for Support Vector Machines
Allan Grønlund, Lior Kamma, Kasper Green Larsen
Poster
Tue 13:00 Generalization to New Actions in Reinforcement Learning
Ayush Jain, Andrew Szot, Joseph Lim
Poster
Tue 14:00 Simple and sharp analysis of k-means||
Vaclav Rozhon
Poster
Tue 14:00 Extreme Multi-label Classification from Aggregated Labels
Yanyao Shen, Hsiang-Fu Yu, Sujay Sanghavi, Inderjit Dhillon
Poster
Tue 14:00 Interpretable, Multidimensional, Multimodal Anomaly Detection with Negative Sampling for Detection of Device Failure
John Sipple
Poster
Tue 14:00 Training Neural Networks for and by Interpolation
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
Poster
Tue 15:00 Interferometric Graph Transform: a Deep Unsupervised Graph Representation
Edouard Oyallon
Poster
Tue 18:00 Learning with Feature and Distribution Evolvable Streams
Zhen-Yu Zhang, Peng Zhao, Yuan Jiang, Zhi-Hua Zhou
Poster
Tue 18:00 Logistic Regression for Massive Data with Rare Events
HaiYing Wang
Poster
Tue 19:00 Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels
Yu-Ting Chou, Gang Niu, Hsuan-Tien Lin, Masashi Sugiyama
Poster
Wed 5:00 Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective
Ruixiang ZHANG, Masanori Koyama, Katsuhiko Ishiguro
Poster
Wed 5:00 SIGUA: Forgetting May Make Learning with Noisy Labels More Robust
Bo Han, Gang Niu, Xingrui Yu, QUANMING YAO, Miao Xu, Ivor Tsang, Masashi Sugiyama
Poster
Wed 5:00 Label-Noise Robust Domain Adaptation
Xiyu Yu, Tongliang Liu, Mingming Gong, Kun Zhang, Kayhan Batmanghelich, Dacheng Tao
Poster
Wed 5:00 Robust Bayesian Classification Using An Optimistic Score Ratio
Viet Anh Nguyen, Nian Si, Jose Blanchet
Poster
Wed 5:00 Median Matrix Completion: from Embarrassment to Optimality
Weidong Liu, Xiaojun Mao, Raymond K. W. Wong
Poster
Wed 5:00 Stabilizing Transformers for Reinforcement Learning
Emilio Parisotto, Francis Song, Jack Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell
Poster
Wed 5:00 Variational Label Enhancement
Ning Xu, Jun Shu, Yun-Peng Liu, Xin Geng
Poster
Wed 5:00 TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Alexander Tong, Jessie Huang, Guy Wolf, David van Dijk, Smita Krishnaswamy
Poster
Wed 5:00 Preference Modeling with Context-Dependent Salient Features
Amanda Bower, Laura Balzano
Poster
Wed 5:00 On Learning Language-Invariant Representations for Universal Machine Translation
Han Zhao, Junjie Hu, Andrej Risteski
Poster
Wed 5:00 Convolutional dictionary learning based auto-encoders for natural exponential-family distributions
Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba
Poster
Wed 5:00 Robust and Stable Black Box Explanations
Hima Lakkaraju, Nino Arsov, Osbert Bastani
Poster
Wed 8:00 Understanding Self-Training for Gradual Domain Adaptation
Ananya Kumar, Tengyu Ma, Percy Liang
Poster
Wed 8:00 Choice Set Optimization Under Discrete Choice Models of Group Decisions
Kiran Tomlinson, Austin Benson
Poster
Wed 8:00 Black-box Certification and Learning under Adversarial Perturbations
Hassan Ashtiani, Vinayak Pathak, Ruth Urner
Poster
Wed 8:00 Sparse Shrunk Additive Models
guodong liu, Hong Chen, Heng Huang
Poster
Wed 8:00 Approximation Capabilities of Neural ODEs and Invertible Residual Networks
Han Zhang, Xi Gao, Jacob Unterman, Tom Arodz
Poster
Wed 8:00 Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification
Hui Ye, Zhiyu Chen, Da-Han Wang, Brian D Davison
Poster
Wed 8:00 Class-Weighted Classification: Trade-offs and Robust Approaches
Neil Xu, Chen Dan, Justin Khim, Pradeep Ravikumar
Poster
Wed 8:00 Strength from Weakness: Fast Learning Using Weak Supervision
Joshua Robinson, Stefanie Jegelka, Suvrit Sra
Poster
Wed 8:00 Coresets for Clustering in Graphs of Bounded Treewidth
Daniel Baker, Vladimir Braverman, Lingxiao Huang, Shaofeng H.-C. Jiang, Robert Krauthgamer, Xuan Wu
Poster
Wed 8:00 Planning to Explore via Self-Supervised World Models
Ramanan Sekar, Oleg Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, Deepak Pathak
Poster
Wed 8:00 Negative Sampling in Semi-Supervised learning
John Chen, Vatsal Shah, Tasos Kyrillidis
Poster
Wed 8:00 Sets Clustering
Ibrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman
Poster
Wed 8:00 Optimizing Black-box Metrics with Adaptive Surrogates
Qijia Jiang, Olaoluwa Adigun, Harikrishna Narasimhan, Mahdi Milani Fard, Maya Gupta
Poster
Wed 9:00 Optimal Sequential Maximization: One Interview is Enough!
Moein Falahatgar, Alon Orlitsky, Venkatadheeraj Pichapati
Poster
Wed 9:00 On the consistency of top-k surrogate losses
Forest Yang, Sanmi Koyejo
Poster
Wed 9:00 Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten Borgwardt
Poster
Wed 9:00 Hallucinative Topological Memory for Zero-Shot Visual Planning
Kara Liu, Thanard Kurutach, Christine Tung, Pieter Abbeel, Aviv Tamar
Poster
Wed 9:00 Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability
Mingjie Li, Lingshen He, Zhouchen Lin
Poster
Wed 10:00 Test-Time Training with Self-Supervision for Generalization under Distribution Shifts
Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei Efros, Moritz Hardt
Poster
Wed 10:00 The Sample Complexity of Best-$k$ Items Selection from Pairwise Comparisons
Wenbo Ren, Jia Liu, Ness Shroff
Poster
Wed 10:00 Small-GAN: Speeding up GAN Training using Core-Sets
Samrath Sinha, Han Zhang, Anirudh Goyal, Yoshua Bengio, Hugo Larochelle, Augustus Odena
Poster
Wed 10:00 Single Point Transductive Prediction
Nilesh Tripuraneni, Lester Mackey
Poster
Wed 10:00 Self-supervised Label Augmentation via Input Transformations
Hankook Lee, Sung Ju Hwang, Jinwoo Shin
Poster
Wed 10:00 Time-Consistent Self-Supervision for Semi-Supervised Learning
Tianyi Zhou, Shengjie Wang, Jeff Bilmes
Poster
Wed 10:00 Correlation Clustering with Asymmetric Classification Errors
Jafar Jafarov, Sanchit Kalhan, Kostya Makarychev, Yury Makarychev
Poster
Wed 11:00 Multidimensional Shape Constraints
Maya Gupta, Erez Louidor, Oleksandr Mangylov, Nobu Morioka, Taman Narayan, Sen Zhao
Poster
Wed 11:00 Robust Graph Representation Learning via Neural Sparsification
Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang
Poster
Wed 11:00 Feature Selection using Stochastic Gates
Yutaro Yamada, Ofir Lindenbaum, Sahand Negahban, Yuval Kluger
Poster
Wed 11:00 Proving the Lottery Ticket Hypothesis: Pruning is All You Need
Eran Malach, Gilad Yehudai, Shai Shalev-Schwartz, Ohad Shamir
Poster
Wed 12:00 Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors
Yehuda Dar, Paul Mayer, Lorenzo Luzi, Richard Baraniuk
Poster
Wed 12:00 Towards a General Theory of Infinite-Width Limits of Neural Classifiers
Eugene Golikov
Poster
Wed 12:00 k-means++: few more steps yield constant approximation
Davin Choo, Christoph Grunau, Julian Portmann, Vaclav Rozhon
Poster
Wed 12:00 Too Relaxed to Be Fair
Michael Lohaus, Michaël Perrot, Ulrike von Luxburg
Poster
Wed 12:00 T-Basis: a Compact Representation for Neural Networks
Anton Obukhov, Maxim Rakhuba, Stamatios Georgoulis, Menelaos Kanakis, Dengxin Dai, Luc Van Gool
Poster
Wed 12:00 Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet
Poster
Wed 12:00 Curvature-corrected learning dynamics in deep neural networks
Dongsung Huh
Poster
Wed 13:00 On the Sample Complexity of Adversarial Multi-Source PAC Learning
Nikola Konstantinov, Elias Frantar, Dan Alistarh, Christoph H. Lampert
Poster
Wed 13:00 Interference and Generalization in Temporal Difference Learning
Emmanuel Bengio, Joelle Pineau, Doina Precup
Poster
Wed 13:00 Growing Adaptive Multi-hyperplane Machines
Nemanja Djuric, Zhuang Wang, Slobodan Vucetic
Poster
Wed 13:00 Adding seemingly uninformative labels helps in low data regimes
Christos Matsoukas, Albert Bou Hernandez, Yue Liu, Karin Dembrower, Gisele Miranda, Emir Konuk, Johan Fredin Haslum, Athanasios Zouzos, Peter Lindholm, Fredrik Strand, Kevin Smith
Poster
Wed 13:00 Student-Teacher Curriculum Learning via Reinforcement Learning: Predicting Hospital Inpatient Admission Location
Rasheed El-Bouri, David Eyre, Peter Watkinson, Tingting Zhu, David Clifton
Poster
Wed 13:00 Generalisation error in learning with random features and the hidden manifold model
Federica Gerace, Bruno Loureiro, Florent Krzakala, Marc Mezard, Lenka Zdeborova
Poster
Wed 13:00 Scalable and Efficient Comparison-based Search without Features
Daniyar Chumbalov, Lucas Maystre, Matt Grossglauser
Poster
Wed 13:00 Boosting Frank-Wolfe by Chasing Gradients
Cyrille W. Combettes, Sebastian Pokutta
Poster
Wed 14:00 Small Data, Big Decisions: Model Selection in the Small-Data Regime
Jorg Bornschein, Francesco Visin, Simon Osindero
Poster
Wed 14:00 Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems
Filip Hanzely, Dmitry Kovalev, Peter Richtarik
Poster
Wed 14:00 It's Not What Machines Can Learn, It's What We Cannot Teach
Gal Yehuda, Moshe Gabel, Assaf Schuster
Poster
Wed 15:00 XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning
Sung Whan Yoon, Do-Yeon Kim, Jun Seo, Jaekyun Moon
Poster
Wed 16:00 Graph-based, Self-Supervised Program Repair from Diagnostic Feedback
Michihiro Yasunaga, Percy Liang
Poster
Wed 16:00 Feature-map-level Online Adversarial Knowledge Distillation
Inseop Chung, SeongUk Park, Kim Jangho, NOJUN KWAK
Poster
Wed 16:00 Spread Divergence
Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber
Poster
Wed 16:00 On Lp-norm Robustness of Ensemble Decision Stumps and Trees
Yihan Wang, Huan Zhang, Hongge Chen, Duane Boning, Cho-Jui Hsieh
Poster
Thu 6:00 Deep Reinforcement Learning with Smooth Policy
Qianli Shen, Yan Li, Haoming Jiang, Zhaoran Wang, Tuo Zhao
Poster
Thu 6:00 Performative Prediction
Juan Perdomo, Tijana Zrnic, Celestine Mendler-Dünner, Moritz Hardt
Poster
Thu 6:00 Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation
Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates
Poster
Thu 6:00 Enhancing Simple Models by Exploiting What They Already Know
Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss
Poster
Thu 6:00 Input-Sparsity Low Rank Approximation in Schatten Norm
Yi Li, David Woodruff
Poster
Thu 6:00 Learning Robot Skills with Temporal Variational Inference
Tanmay Shankar, Abhinav Gupta
Poster
Thu 6:00 p-Norm Flow Diffusion for Local Graph Clustering
Kimon Fountoulakis, Di Wang, Shenghao Yang
Poster
Thu 6:00 Learning with Bounded Instance- and Label-dependent Label Noise
Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao, Dacheng Tao
Poster
Thu 6:00 Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization
Quoc Tran-Dinh, Nate H Pham, Lam Nguyen
Poster
Thu 6:00 Fiedler Regularization: Learning Neural Networks with Graph Sparsity
Edric Tam, David Dunson
Poster
Thu 6:00 Countering Language Drift with Seeded Iterated Learning
Yuchen Lu, Soumye Singhal, Florian Strub, Aaron Courville, Olivier Pietquin
Poster
Thu 6:00 Sequence Generation with Mixed Representations
Lijun Wu, Shufang Xie, Yingce Xia, Yang Fan, Jian-Huang Lai, Tao Qin, Tie-Yan Liu
Poster
Thu 6:00 Does label smoothing mitigate label noise?
Michal Lukasik, Srinadh Bhojanapalli, Aditya Menon, Sanjiv Kumar
Poster
Thu 6:00 PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions
Zhengyang Shen, Lingshen He, Zhouchen Lin, Jinwen Ma
Poster
Thu 6:00 Tails of Lipschitz Triangular Flows
Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker
Poster
Thu 6:00 Error-Bounded Correction of Noisy Labels
Songzhu Zheng, Pengxiang Wu, Aman Goswami, Mayank Goswami, Dimitris Metaxas, Chao Chen
Poster
Thu 6:00 Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon, Abdul Canatar, Cengiz Pehlevan
Poster
Thu 6:00 How to Train Your Neural ODE: the World of Jacobian and Kinetic Regularization
Chris Finlay, Jörn Jacobsen, Levon Nurbekyan, Adam Oberman
Poster
Thu 6:00 Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li, Sekhar Tatikonda, Xenophon Papademetris, James Duncan
Poster
Thu 6:00 Bridging the Gap Between f-GANs and Wasserstein GANs
Jiaming Song, Stefano Ermon
Poster
Thu 6:00 Task Understanding from Confusing Multi-task Data
Xin Su, Yizhou Jiang, Shangqi Guo, Feng Chen
Poster
Thu 6:00 Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang, Phillip Isola
Poster
Thu 6:00 A Pairwise Fair and Community-preserving Approach to k-Center Clustering
Brian Brubach, Darshan Chakrabarti, John P Dickerson, Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas
Poster
Thu 6:00 Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models
Rares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag
Poster
Thu 6:00 Convex Calibrated Surrogates for the Multi-Label F-Measure
Mingyuan Zhang, Harish Ramaswamy, Shivani Agarwal
Poster
Thu 6:00 Graph Homomorphism Convolution
Hoang NT, Takanori Maehara
Poster
Thu 7:00 Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates
Jeff Calder, Brendan Cook, Matthew Thorpe, Dejan Slepcev
Poster
Thu 7:00 Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit Patel, Anima Anandkumar
Poster
Thu 7:00 Semi-Supervised Learning with Normalizing Flows
Pavel Izmailov, Polina Kirichenko, Marc Finzi, Andrew Wilson
Poster
Thu 7:00 Distribution Augmentation for Generative Modeling
Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever
Poster
Thu 7:00 Learning Discrete Structured Representations by Adversarially Maximizing Mutual Information
Karl Stratos, Sam Wiseman
Poster
Thu 7:00 Improving generalization by controlling label-noise information in neural network weights
Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan
Poster
Thu 7:00 Normalized Loss Functions for Deep Learning with Noisy Labels
Xingjun Ma, Curtis Huang, Yisen Wang, Simone Romano, Sarah Erfani, James Bailey
Poster
Thu 7:00 Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation
Xiang Jiang, Qicheng Lao, Stan Matwin, Mohammad Havaei
Poster
Thu 7:00 Simultaneous Inference for Massive Data: Distributed Bootstrap
Yang Yu, Shih-Kang Chao, Guang Cheng
Poster
Thu 7:00 On hyperparameter tuning in general clustering problemsm
Xinjie Fan, Yuguang Yue, Purnamrita Sarkar, Y. X. Rachel Wang
Poster
Thu 7:00 Efficient Continuous Pareto Exploration in Multi-Task Learning
Pingchuan Ma, Tao Du, Wojciech Matusik
Poster
Thu 7:00 Uniform Convergence of Rank-weighted Learning
Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar
Poster
Thu 7:00 Kinematic State Abstraction and Provably Efficient Rich-Observation Reinforcement Learning
Dipendra Kumar Misra, Mikael Henaff, Akshay Krishnamurthy, John Langford
Poster
Thu 7:00 ACFlow: Flow Models for Arbitrary Conditional Likelihoods
Yang Li, Shoaib Akbar, Junier Oliva
Poster
Thu 8:00 Learning Mixtures of Graphs from Epidemic Cascades
Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis
Poster
Thu 8:00 Principled learning method for Wasserstein distributionally robust optimization with local perturbations
Yongchan Kwon, Wonyoung Kim, Joong-Ho (Johann) Won, Myunghee Cho Paik
Poster
Thu 8:00 Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Wei Deng, Qi Feng, Liyao Gao, Faming Liang, Guang Lin
Poster
Thu 8:00 Domain Aggregation Networks for Multi-Source Domain Adaptation
Junfeng Wen, Russell Greiner, Dale Schuurmans
Poster
Thu 8:00 Progressive Identification of True Labels for Partial-Label Learning
Jiaqi Lv, Miao Xu, LEI FENG, Gang Niu, Xin Geng, Masashi Sugiyama
Poster
Thu 8:00 One-shot Distributed Ridge Regression in High Dimensions
Yue Sheng, Edgar Dobriban
Poster
Thu 9:00 Decision Trees for Decision-Making under the Predict-then-Optimize Framework
Adam Elmachtoub, Jason Cheuk Nam Liang, Ryan McNellis
Poster
Thu 9:00 Unsupervised Discovery of Interpretable Directions in the GAN Latent Space
Andrey Voynov, Artem Babenko
Poster
Thu 9:00 A Distributional Framework For Data Valuation
Amirata Ghorbani, Michael Kim, James Zou
Poster
Thu 9:00 Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation
Georgios Smyrnis, Petros Maragos
Poster
Thu 9:00 The Implicit Regularization of Stochastic Gradient Flow for Least Squares
Alnur Ali, Edgar Dobriban, Ryan Tibshirani
Poster
Thu 9:00 Generalization Error of Generalized Linear Models in High Dimensions
Melika Emami, Moji Sahraee-Ardakan, Parthe Pandit, Sundeep Rangan, Alyson Fletcher
Poster
Thu 9:00 When Does Self-Supervision Help Graph Convolutional Networks?
Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen
Poster
Thu 9:00 Bio-Inspired Hashing for Unsupervised Similarity Search
Chaitanya Ryali, John Hopfield, Leopold Grinberg, Dmitry Krotov
Poster
Thu 12:00 PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, Peter Liu
Poster
Thu 12:00 Supervised Quantile Normalization for Low Rank Matrix Factorization
Marco Cuturi, Olivier Teboul, Jonathan Niles-Weed, JP Vert
Poster
Thu 12:00 Aggregation of Multiple Knockoffs
Tuan-Binh Nguyen, Jerome-Alexis Chevalier, Thirion Bertrand, Sylvain Arlot
Poster
Thu 12:00 Online Continual Learning from Imbalanced Data
Aristotelis Chrysakis, Marie-Francine Moens
Poster
Thu 12:00 Missing Data Imputation using Optimal Transport
Boris Muzellec, Julie Josse, Claire Boyer, Marco Cuturi
Poster
Thu 12:00 Optimistic Bounds for Multi-output Learning
Henry Reeve, Ata Kaban
Poster
Thu 12:00 Data-Efficient Image Recognition with Contrastive Predictive Coding
Olivier Henaff
Poster
Thu 12:00 Topologically Densified Distributions
Christoph Hofer, Florian Graf, Marc Niethammer, Roland Kwitt
Poster
Thu 13:00 Robust Learning with the Hilbert-Schmidt Independence Criterion
Daniel Greenfeld, Uri Shalit
Poster
Thu 13:00 On Efficient Low Distortion Ultrametric Embedding
Vincent Cohen-Addad, Karthik C. S., Guillaume Lagarde
Poster
Thu 13:00 Graph Filtration Learning
Christoph Hofer, Florian Graf, Bastian Rieck, Marc Niethammer, Roland Kwitt
Poster
Thu 13:00 Topic Modeling via Full Dependence Mixtures
Dan Fisher, Mark Kozdoba, Shie Mannor
Poster
Thu 13:00 Convolutional Kernel Networks for Graph-Structured Data
Dexiong Chen, Laurent Jacob, Julien Mairal
Poster
Thu 13:00 Predicting Choice with Set-Dependent Aggregation
Nir Rosenfeld, Kojin Oshiba, Yaron Singer
Poster
Thu 13:00 Stochastic Subspace Cubic Newton Method
Filip Hanzely, Nikita Doikov, Yurii Nesterov, Peter Richtarik
Poster
Thu 13:00 Amortised Learning by Wake-Sleep
Kevin Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani
Poster
Thu 15:00 Deep Streaming Label Learning
Zhen Wang, Liu Liu, Dacheng Tao
Poster
Thu 15:00 Stochastic Optimization for Regularized Wasserstein Estimators
Marin Ballu, Quentin Berthet, Francis Bach
Poster
Thu 17:00 DropNet: Reducing Neural Network Complexity via Iterative Pruning
Chong Min John Tan, Mehul Motani
Poster
Thu 17:00 More Information Supervised Probabilistic Deep Face Embedding Learning
Ying Huang, Shangfeng Qiu, Wenwei Zhang, Xianghui Luo, Jinzhuo Wang
Poster
Thu 17:00 Self-Attentive Associative Memory
Hung Le, Truyen Tran, Svetha Venkatesh
Poster
Thu 17:00 Sparse Subspace Clustering with Entropy-Norm
Liang Bai, Jiye Liang
Poster
Thu 18:00 Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training
Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gong, Kewei Chen, Zhangyang Wang
Workshop
Thu 23:45 XXAI: Extending Explainable AI Beyond Deep Models and Classifiers
Wojciech Samek, Andreas HOLZINGER, Ruth Fong, Taesup Moon, Klaus-robert Mueller
Workshop
Fri 0:05 Self-supervision in Audio and Speech
Mirco Ravanelli, Dmitriy Serdyuk, R Devon Hjelm, Bhuvana Ramabhadran, Titouan Parcollet
Workshop
Fri 0:15 Invited Talk: Representation learning on sequential data with latent priors
Jan Chorowski
Workshop
Fri 1:45 Investigating Self-supervised Pre-training for End-to-end Speech Translation
Ha Nguyen
Workshop
Fri 4:00 Invited Talk: Denoising and real-vs-corrupted classification as two fundamental paradigms in self-supervised learning
Aapo Hyvarinen
Workshop
Fri 5:15 Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision
Abhinav Shukla
Workshop
Fri 6:00 Workshop on eXtreme Classification: Theory and Applications
Anna Choromanska, John Langford, Maryam Majzoubi, Yashoteja Prabhu
Workshop
Fri 6:00 End-to-End ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
Jacob Kahn
Workshop
Fri 6:15 Using Self-Supervised Learning of Birdsong for Downstream Industrial Audio Classification
Patty Ryan
Workshop
Fri 7:05 COVID-19 Applications: Gaining insight into SARS-CoV-2 infection and COVID-19 severity using self-supervised edge features and Graph Neural Networks
Arijit Sehanobish
Workshop
Fri 7:45 Invited Talk: Self-supervised learning of speech representations with wav2vec
Alexei Baevski
Workshop
Fri 8:55 Unsupervised Speech Separation Using Mixtures of Mixtures
Scott Wisdom
Workshop
Fri 9:00 Poster Session (click to see links)
Workshop
Fri 14:15 [Session 2] P#18 Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning
Workshop
Fri 14:40 Energy-Based Models for Object-Oriented Learning
Igor Mordatch
Workshop
Sat 2:00 4th Lifelong Learning Workshop
Shagun Sodhani, Sarath Chandar, Balaraman Ravindran, Doina Precup
Workshop
Sat 6:35 Technical Talks Session 1
Ishika Singh, Laura Rieger, Rasmus Høegh, Hanlin Lu, Wonyong Jeong
Workshop
Sat 7:15 Invited Talk: Lifelong Learning: Towards Broad and Robust AI by Irina Rish
Irina Rish
Workshop
Sat 7:35 An Unsupervised Learning Approach to Mitigate the Risk of Polio Recurrence in India
Tushar Goswamy
Workshop
Sat 8:20 Posters
Workshop
Sat 10:20 Keynote Session 3: Federated Learning Applications in Alexa, by Shiv Vitaladevuni (Amazon Alexa)
Shiv Vitaladevuni
Workshop
(#86 / Sess. 2) Graph Generation with Energy-Based Models
Jenny Liu
Workshop
(#73 / Sess. 2) Evaluating Logical Generalization in Graph Neural Networks
Koustuv Sinha
Workshop
(#15 / Sess. 2) Learning Distributed Representations of Graphs with Geo2DR
Paul Scherer