136 Results

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 Learning from Irregularly-Sampled Time Series: A Missing Data Perspective
Steve Li, Benjamin M Marlin
Poster
Tue 7:00 Interpolation between Residual and Non-Residual Networks
Zonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi
Poster
Tue 7:00 Two Routes to Scalable Credit Assignment without Weight Symmetry
Daniel Kunin, Aran Nayebi, Javier Sagastuy-Brena, Surya Ganguli, Jon Bloom, Daniel Yamins
Poster
Tue 7:00 Confidence-Aware Learning for Deep Neural Networks
Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang
Poster
Tue 7:00 PENNI: Pruned Kernel Sharing for Efficient CNN Inference
Shiyu Li, Edward Hanson, Hai Li, Yiran Chen
Poster
Tue 7:00 AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
Yonggan Fu, Wuyang Chen, Haotao Wang, Haoran Li, Yingyan Lin, Zhangyang 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 Maximum-and-Concatenation Networks
Xingyu Xie, Hao Kong, Jianlong Wu, Wayne Zhang, Guangcan Liu, Zhouchen Lin
Poster
Tue 7:00 Multigrid Neural Memory
Tri Huynh, Michael Maire, Matthew Walter
Poster
Tue 8:00 Neural Clustering Processes
Ari Pakman, Yueqi Wang, Catalin Mitelut, JinHyung Lee, Department of Statistics Liam Paninski
Poster
Tue 8:00 Detecting Out-of-Distribution Examples with Gram Matrices
Chandramouli Shama Sastry, Sageev Oore
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 NADS: Neural Architecture Distribution Search for Uncertainty Awareness
Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian
Poster
Tue 8:00 Working Memory Graphs
Ricky Loynd, Roland Fernandez, Asli Celikyilmaz, Adith Swaminathan, Matthew Hausknecht
Poster
Tue 9:00 Stabilizing Differentiable Architecture Search via Perturbation-based Regularization
Xiangning Chen, Cho-Jui Hsieh
Poster
Tue 9:00 Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Iris Yu, Jianfeng Gao, Changyou Chen
Poster
Tue 9:00 Disentangling Trainability and Generalization in Deep Neural Networks
Lechao Xiao, Jeffrey Pennington, Samuel Schoenholz
Poster
Tue 10:00 Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
Felipe Petroski Such, Aditya Rawal, Joel Lehman, Ken Stanley, Jeffrey Clune
Poster
Tue 10:00 Deep Isometric Learning for Visual Recognition
Haozhi Qi, Chong You, Xiaolong Wang, Yi Ma, Jitendra Malik
Poster
Tue 10:00 Generalizing Convolutional Neural Networks for Equivariance to Lie Groups on Arbitrary Continuous Data
Marc Finzi, Samuel Stanton, Pavel Izmailov, Andrew Wilson
Poster
Tue 10:00 Revisiting Spatial Invariance with Low-Rank Local Connectivity
Gamaleldin Elsayed, Prajit Ramachandran, Jon Shlens, Simon Kornblith
Poster
Tue 10:00 On Learning Sets of Symmetric Elements
Haggai Maron, Or Litany, Gal Chechik, Ethan Fetaya
Poster
Tue 10:00 Learning To Stop While Learning To Predict
Xinshi Chen, Hanjun Dai, Yu Li, Xin Gao, Le Song
Poster
Tue 11:00 Information-Theoretic Local Minima Characterization and Regularization
Zhiwei Jia, Hao Su
Poster
Tue 12:00 Learning disconnected manifolds: a no GAN's land
Ugo Tanielian, Thibaut Issenhuth, Elvis Dohmatob, Jeremie Mary
Poster
Tue 12:00 Word-Level Speech Recognition With a Letter to Word Encoder
Ronan Collobert, Awni Hannun, Gabriel Synnaeve
Poster
Tue 13:00 Linear Mode Connectivity and the Lottery Ticket Hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel Roy, Michael Carbin
Poster
Tue 13:00 An Explicitly Relational Neural Network Architecture
Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David GT Barrett, Marta Garnelo
Poster
Tue 13:00 GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
Marc Brockschmidt
Poster
Tue 13:00 Constant Curvature Graph Convolutional Networks
Gregor Bachmann, Gary Becigneul, Octavian Ganea
Poster
Tue 13:00 Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities
Jonas Köhler, Leon Klein, Frank Noe
Poster
Tue 14:00 Training Neural Networks for and by Interpolation
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
Poster
Tue 14:00 Finding trainable sparse networks through Neural Tangent Transfer
Tianlin Liu, Friedemann Zenke
Poster
Tue 14:00 Infinite attention: NNGP and NTK for deep attention networks
Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein, Roman Novak
Poster
Tue 14:00 Voice Separation with an Unknown Number of Multiple Speakers
Eliya Nachmani, Yossi Adi, Lior Wolf
Poster
Tue 14:00 Why bigger is not always better: on finite and infinite neural networks
Laurence Aitchison
Poster
Wed 5:00 Channel Equilibrium Networks for Learning Deep Representation
Wenqi Shao, Shitao Tang, Xingang Pan, Ping Tan, Xiaogang Wang, Ping Luo
Poster
Wed 5:00 Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
Filipe de Avila Belbute-Peres, Thomas Economon, Zico Kolter
Poster
Wed 5:00 Operation-Aware Soft Channel Pruning using Differentiable Masks
Minsoo Kang, Bohyung Han
Poster
Wed 5:00 Neural Architecture Search in A Proxy Validation Loss Landscape
Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu
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 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 8:00 Approximation Capabilities of Neural ODEs and Invertible Residual Networks
Han Zhang, Xi Gao, Jacob Unterman, Tom Arodz
Poster
Wed 8:00 Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network
Javier Turek, Shailee Jain, Vy Vo, Mihai Capotă, Alexander Huth, Theodore Willke
Poster
Wed 8:00 Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang, Mingkui Tan
Poster
Wed 8:00 Boosting Deep Neural Network Efficiency with Dual-Module Inference
Liu Liu, Lei Deng, Zhaodong Chen, yuke wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie
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 Representing Unordered Data Using Complex-Weighted Multiset Automata
Justin DeBenedetto, David Chiang
Poster
Wed 9:00 Adversarial Robustness Against the Union of Multiple Perturbation Models
Pratyush Maini, Eric Wong, Zico Kolter
Poster
Wed 9:00 Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten Borgwardt
Poster
Wed 9:00 SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
Lingkai Kong, Jimeng Sun, Chao Zhang
Poster
Wed 9:00 Implicit Euler Skip Connections: Enhancing Adversarial Robustness via Numerical Stability
Mingjie Li, Lingshen He, Zhouchen Lin
Poster
Wed 10:00 Learning Representations that Support Extrapolation
Taylor Webb, Zachary Dulberg, Steven Frankland, Alexander Petrov, Randall O'Reilly, Jonathan Cohen
Poster
Wed 10:00 Data Valuation using Reinforcement Learning
Jinsung Yoon, Sercan Arik, Tomas Pfister
Poster
Wed 11:00 Fairwashing explanations with off-manifold detergent
Christopher Anders, Plamen Pasliev, Ann-Kathrin Dombrowski, Klaus-robert Mueller, Pan Kessel
Poster
Wed 11:00 PolyGen: An Autoregressive Generative Model of 3D Meshes
Charlie Nash, Yaroslav Ganin, S. M. Ali Eslami, Peter Battaglia
Poster
Wed 11:00 The Implicit and Explicit Regularization Effects of Dropout
Colin Wei, Sham Kakade, Tengyu Ma
Poster
Wed 11:00 Deep Gaussian Markov Random Fields
Per Sidén, Fredrik Lindsten
Poster
Wed 12:00 Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows
Rob Cornish, Anthony Caterini, George Deligiannidis, Arnaud Doucet
Poster
Wed 12:00 CoMic: Complementary Task Learning & Mimicry for Reusable Skills
Leonard Hasenclever, Fabio Pardo, Raia Hadsell, Nicolas Heess, Josh Merel
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 Learning to Encode Position for Transformer with Continuous Dynamical Model
Xuanqing Liu, Hsiang-Fu Yu, Inderjit Dhillon, Cho-Jui Hsieh
Poster
Wed 12:00 Equivariant Neural Rendering
Emilien Dupont, Miguel Angel Bautista Martin, Alex Colburn, Aditya Sankar, Josh M Susskind, Qi Shan
Poster
Wed 12:00 Radioactive data: tracing through training
Alexandre Sablayrolles, Douze Matthijs, Cordelia Schmid, Herve Jegou
Poster
Wed 13:00 A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits
Ramin Hasani, Mathias Lechner, Alexander Amini, Daniela Rus, Radu Grosu
Poster
Wed 13:00 Leveraging Frequency Analysis for Deep Fake Image Recognition
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz
Poster
Wed 13:00 Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
Angelos Katharopoulos, Apoorv Vyas, Nikolaos Pappas, François Fleuret
Poster
Wed 13:00 Attentive Group Equivariant Convolutional Networks
David Romero, Erik Bekkers, Jakub Tomczak, Mark Hoogendoorn
Poster
Wed 14:00 VideoOneNet: Bidirectional Convolutional Recurrent OneNet with Trainable Data Steps for Video Processing
Zoltán Á. Milacski, Barnabás Póczos, Andras Lorincz
Poster
Wed 14:00 Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets
Guy Hacohen, Leshem Choshen, Daphna Weinshall
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 DeepCoDA: personalized interpretability for compositional health data
Thomas Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
Poster
Wed 14:00 Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs
Aditya Rajagopal, Diederik Vink, Stylianos Venieris, Christos-Savvas Bouganis
Poster
Wed 15:00 Haar Graph Pooling
Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar, Xiaosheng Zhuang, Yanan Fan
Poster
Wed 15:00 Orthogonalized SGD and Nested Architectures for Anytime Neural Networks
Chengcheng Wan, Henry (Hank) Hoffmann, Shan Lu, Michael Maire
Poster
Wed 16:00 Feature-map-level Online Adversarial Knowledge Distillation
Inseop Chung, SeongUk Park, Kim Jangho, NOJUN KWAK
Poster
Thu 6:00 Rigging the Lottery: Making All Tickets Winners
Utku Evci, Trevor Gale, Jacob Menick, Pablo Samuel Castro, Erich Elsen
Poster
Thu 6:00 Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification
Hongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner
Poster
Thu 6:00 Low-Rank Bottleneck in Multi-head Attention Models
Srinadh Bhojanapalli, Chulhee (Charlie) Yun, Ankit Singh Rawat, Sashank Jakkam Reddi, 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 Multi-Agent Routing Value Iteration Network
Quinlan Sykora, Mengye Ren, Raquel Urtasun
Poster
Thu 6:00 Improving Transformer Optimization Through Better Initialization
Xiao Shi Huang, Felipe Perez, Jimmy Ba, Maksims Volkovs
Poster
Thu 6:00 Towards Accurate Post-training Network Quantization via Bit-Split and Stitching
Peisong Wang, Qiang Chen, Xiangyu He, Jian Cheng
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 7:00 Deep Molecular Programming: A Natural Implementation of Binary-Weight ReLU Neural Networks
Marko Vasic, Cameron Chalk, Sarfraz Khurshid, David Soloveichik
Poster
Thu 7:00 Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion
Nghia Hoang, Thanh Lam, Bryan Kian Hsiang Low, Patrick Jaillet
Poster
Thu 7:00 Graph Structure of Neural Networks
Jiaxuan You, Jure Leskovec, Kaiming He, Saining Xie
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 Go Wide, Then Narrow: Efficient Training of Deep Thin Networks
Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc Le, Qiang Liu, Dale Schuurmans
Poster
Thu 7:00 Perceptual Generative Autoencoders
Zijun Zhang, Ruixiang ZHANG, Zongpeng Li, Yoshua Bengio, Liam Paull
Poster
Thu 7:00 Lorentz Group Equivariant Neural Network for Particle Physics
Alexander Bogatskiy, Brandon Anderson, Jan T Offermann, Marwah Roussi, David Miller, Risi Kondor
Poster
Thu 7:00 Time-aware Large Kernel Convolutions
Vasileios Lioutas, Yuhong Guo
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 8:00 Sparse Sinkhorn Attention
Yi Tay, Dara Bahri, Liu Yang, Don Metzler, Da-Cheng Juan
Poster
Thu 8:00 Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels
Lu Jiang, Di Huang, Mason Liu, Weilong Yang
Poster
Thu 9:00 Inferring DQN structure for high-dimensional continuous control
Andrey Sakryukin, Chedy Raissi, Mohan Kankanhalli
Poster
Thu 9:00 Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection
Mao Ye, Chengyue Gong, Lizhen Nie, Denny Zhou, Adam Klivans, Qiang Liu
Poster
Thu 12:00 Neural Kernels Without Tangents
Vaishaal Shankar, Alex Fang, Wenshuo Guo, Sara Fridovich-Keil, Jonathan Ragan-Kelley, Ludwig Schmidt, Benjamin Recht
Poster
Thu 12:00 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
Poster
Thu 12:00 Revisiting Training Strategies and Generalization Performance in Deep Metric Learning
Karsten Roth, Timo Milbich, Samrath Sinha, Prateek Gupta, Bjorn Ommer, Joseph Paul Cohen
Poster
Thu 12:00 Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
Poster
Thu 12:00 Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural Networks
Alexander Shevchenko, Marco Mondelli
Poster
Thu 12:00 Soft Threshold Weight Reparameterization for Learnable Sparsity
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi
Poster
Thu 12:00 Online Continual Learning from Imbalanced Data
Aristotelis Chrysakis, Marie-Francine Moens
Poster
Thu 12:00 PowerNorm: Rethinking Batch Normalization in Transformers
Sheng Shen, Zhewei Yao, Amir Gholaminejad, Michael Mahoney, Kurt Keutzer
Poster
Thu 13:00 Spectral Clustering with Graph Neural Networks for Graph Pooling
Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi
Poster
Thu 13:00 Graph Filtration Learning
Christoph Hofer, Florian Graf, Bastian Rieck, Marc Niethammer, Roland Kwitt
Poster
Thu 13:00 Latent Bernoulli Autoencoder
Jiri Fajtl, Vasileios Argyriou, Dorothy Monekosso, Paolo Remagnino
Poster
Thu 13:00 Learning to Branch for Multi-Task Learning
Pengsheng Guo, Chen-Yu Lee, Daniel Ulbricht
Poster
Thu 14:00 Inducing and Exploiting Activation Sparsity for Fast Inference on Deep Neural Networks
Mark Kurtz, Justin Kopinsky, Rati Gelashvili, Alexander Matveev, John Carr, Michael Goin, William Leiserson, Sage Moore, Nir Shavit, Dan Alistarh
Poster
Thu 14:00 Multi-Agent Determinantal Q-Learning
Yaodong Yang, Ying Wen, Jun Wang, Liheng Chen, Kun Shao, David Mguni, Weinan Zhang
Poster
Thu 15:00 Deep Streaming Label Learning
Zhen Wang, Liu Liu, Dacheng Tao
Poster
Thu 17:00 A Tree-Structured Decoder for Image-to-Markup Generation
Jianshu Zhang, Jun Du, Yongxin Yang, Yi-Zhe Song, Si Wei, Lirong Dai
Poster
Thu 17:00 Learning Autoencoders with Relational Regularization
Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin
Poster
Thu 17:00 DropNet: Reducing Neural Network Complexity via Iterative Pruning
Chong Min John Tan, Mehul Motani
Poster
Thu 17:00 Self-Attentive Associative Memory
Hung Le, Truyen Tran, Svetha Venkatesh
Poster
Thu 18:00 On Layer Normalization in the Transformer Architecture
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
Workshop
Fri 1:45 Learning with Missing Values
Julie Josse, Jes Frellsen, Pierre-Alexandre Mattei, Gael Varoquaux
Workshop
Fri 5:00 Workshop on AI for Autonomous Driving (AIAD)
Wei-Lun (Harry) Chao, Rowan McAllister, Adrien Gaidon, Li Erran Li, Sven Kreiss
Workshop
Fri 5:55 System-wide Monitoring Architectures with Explanations
Leilani Gilpin
Workshop
Fri 6:00 End-to-End ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
Jacob Kahn
Workshop
Fri 7:10 Attentive Grouping and Graph Neural Networks for Object-Centric Learning
Thomas Kipf
Workshop
Fri 8:00 Beyond first order methods in machine learning systems
Albert S Berahas, Amir Gholaminejad, Tasos Kyrillidis, Michael Mahoney, Fred Roosta
Workshop
Fri 13:30 Spotlight talk 4 - MomentumRNN: Integrating Momentum into Recurrent Neural Networks
HUNG MINH TAN Nguyen
Workshop
Sat 4:00 Virtual Poster Session #1
Workshop
Sat 6:00 7th ICML Workshop on Automated Machine Learning (AutoML 2020)
Frank Hutter, Joaquin Vanschoren, Marius Lindauer, Charles Weill, Katharina Eggensperger, Matthias Feurer
Workshop
Sat 8:00 Virtual Poster Session #2
Workshop
(#87 / Sess. 2) Bi-Level Attention Neural Architectures for Relational Data
Roshni Iyer
Workshop
(#80 / Sess. 2) Weisfeiler and Leman go sparse: Towards scalable higher-order graph embeddings
Christopher Morris
Workshop
(#77 / Sess. 1) SIGN: Scalable Inception Graph Neural Networks
Fabrizio Frasca
Workshop
(#64 / Sess. 1) Differentiable Graph Module (DGM) for Graph Convolutional Networks
Anees Kazi
Workshop
(#71 / Sess. 1) Population Graph GNNs for Brain Age Prediction
Kamile Stankeviciute
Workshop
Accepted Papers
Workshop
(#21 / Sess. 2) Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions
Michael Maser
Workshop
(#24 / Sess. 2) Degree-Quant: Quantization-Aware Training for Graph Neural Networks
Shyam Tailor