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Expo Workshop
Sun 17:10 PaddleCV: Rich and Practical CV Models from Industrial Practice
Chenxia Li
Expo Workshop
Sun 20:00 Generalizing from a few examples by PaddleFSL
Yaqing Wang
Affinity Workshop
Mon 10:25 A multiple strategy for plant species identification using images of leaf texture
Igor Luidji Turra, Sérgio Francisco Silva, Douglas Cordeiro, Núbia Da Silva
Affinity Workshop
Mon 13:50 Community pooling: LDA topic modeling in Twitter
Federico Albanese
Affinity Workshop
Mon 14:05 Convolutional Neural Networks Evaluation for COVID-19 Classification on Chest Radiographs
Felipe Zeiser, Cristiano André da Costa, Gabriel Ramos
Affinity Workshop
Mon 15:40 Long Short-Term Memory with Slower Information Decay
Hsiang-Yun Chien, Javier Turek, Nicole Beckage, Vy Vo, Christopher Honey, Theodore Willke
Oral
Tue 5:00 Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro
Oral
Tue 5:00 Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa
Oral
Tue 5:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
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 5:20 Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
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 5:25 Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
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 Strategic Classification Made Practical
Sagi Levanon, Nir Rosenfeld
Spotlight
Tue 5:35 From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai, Ethan Fetaya, eli meirom, Gal Chechik, Haggai Maron
Spotlight
Tue 5:40 Sparsifying Networks via Subdifferential Inclusion
Sagar Verma, Jean-Christophe Pesquet
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 5:40 Large-Margin Contrastive Learning with Distance Polarization Regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama
Oral
Tue 6:00 Leveraging Sparse Linear Layers for Debuggable Deep Networks
Eric Wong, Shibani Santurkar, Aleksander Madry
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 Dueling Convex Optimization
Aadirupa Saha, Tomer Koren, Yishay Mansour
Spotlight
Tue 6:20 Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Huck Yang, Yun-Yun Tsai, Pin-Yu Chen
Spotlight
Tue 6:20 Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai
Spotlight
Tue 6:20 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
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 Connecting Sphere Manifolds Hierarchically for Regularization
Damien Scieur, Youngsung Kim
Spotlight
Tue 6:40 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montufar, Pietro Lió, Michael Bronstein
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 6:45 Loss Surface Simplexes for Mode Connecting Volumes and Fast Ensembling
Gregory Benton, Wesley Maddox, Sanae Lotfi, Andrew Wilson
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 7:45 Better Training using Weight-Constrained Stochastic Dynamics
Benedict Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos Storkey
Poster
Tue 9:00 Fundamental Tradeoffs in Distributionally Adversarial Training
Mohammad Mehrabi, Adel Javanmard, Ryan A. Rossi, Anup Rao, Tung Mai
Poster
Tue 9:00 Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Huck Yang, Yun-Yun Tsai, Pin-Yu Chen
Poster
Tue 9:00 Connecting Sphere Manifolds Hierarchically for Regularization
Damien Scieur, Youngsung Kim
Poster
Tue 9:00 Optimal Complexity in Decentralized Training
Yucheng Lu, Christopher De Sa
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 Better Training using Weight-Constrained Stochastic Dynamics
Benedict Leimkuhler, Tiffany Vlaar, Timothée Pouchon, Amos Storkey
Poster
Tue 9:00 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montufar, Pietro Lió, Michael Bronstein
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 A Unified Lottery Ticket Hypothesis for Graph Neural Networks
Tianlong Chen, Yongduo Sui, Xuxi Chen, Aston Zhang, Zhangyang Wang
Poster
Tue 9:00 From Local Structures to Size Generalization in Graph Neural Networks
Gilad Yehudai, Ethan Fetaya, eli meirom, Gal Chechik, Haggai Maron
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 Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
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 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 Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning
Alex Immer, Matthias Bauer, Vincent Fortuin, Gunnar Ratsch, Khan Emtiyaz
Poster
Tue 9:00 Size-Invariant Graph Representations for Graph Classification Extrapolations
Beatrice Bevilacqua, Yangze Zhou, Bruno Ribeiro
Poster
Tue 9:00 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
Poster
Tue 9:00 Sparsifying Networks via Subdifferential Inclusion
Sagar Verma, Jean-Christophe Pesquet
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 Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Georgescu, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
Poster
Tue 9:00 Strategic Classification Made Practical
Sagi Levanon, Nir Rosenfeld
Poster
Tue 9:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Poster
Tue 9:00 Dueling Convex Optimization
Aadirupa Saha, Tomer Koren, Yishay Mansour
Poster
Tue 9:00 Large-Margin Contrastive Learning with Distance Polarization Regularizer
Shuo Chen, Gang Niu, Chen Gong, Jun Li, Jian Yang, Masashi Sugiyama
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 Leveraging Sparse Linear Layers for Debuggable Deep Networks
Eric Wong, Shibani Santurkar, Aleksander Madry
Spotlight
Tue 17:20 Stabilizing Equilibrium Models by Jacobian Regularization
Shaojie Bai, Vladlen Koltun, Zico Kolter
Spotlight
Tue 17:20 What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
Weijian Deng, Stephen Gould, Liang Zheng
Spotlight
Tue 17:25 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
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 18:25 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
Spotlight
Tue 18:35 AutoAttend: Automated Attention Representation Search
Chaoyu Guan, Xin Wang, wenwu zhu
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
Oral
Tue 19:00 ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph E Gonzalez
Spotlight
Tue 19:20 What Makes for End-to-End Object Detection?
Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo
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 A Receptor Skeleton for Capsule Neural Networks
Jintai Chen, Hongyun Yu, Chengde Qian, Danny Z Chen, Jian Wu
Spotlight
Tue 19:25 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Spotlight
Tue 19:30 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
Spotlight
Tue 19:35 Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein
Spotlight
Tue 19:40 High-Performance Large-Scale Image Recognition Without Normalization
Andy Brock, Soham De, Samuel Smith, Karen Simonyan
Spotlight
Tue 19:40 Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
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
Poster
Tue 21:00 ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training
Jianfei Chen, Lianmin Zheng, Zhewei Yao, Dequan Wang, Ion Stoica, Michael Mahoney, Joseph E Gonzalez
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 Lipschitz normalization for self-attention layers with application to graph neural networks
George Dasoulas, Kevin Scaman, Aladin Virmaux
Poster
Tue 21:00 What Makes for End-to-End Object Detection?
Peize Sun, Yi Jiang, Enze Xie, Wenqi Shao, Zehuan Yuan, Changhu Wang, Ping Luo
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 What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
Weijian Deng, Stephen Gould, Liang Zheng
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 Stabilizing Equilibrium Models by Jacobian Regularization
Shaojie Bai, Vladlen Koltun, Zico Kolter
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
Poster
Tue 21:00 Bayesian Optimization over Hybrid Spaces
Aryan Deshwal, Syrine Belakaria, Janardhan Doppa
Poster
Tue 21:00 A Unified Generative Adversarial Network Training via Self-Labeling and Self-Attention
Tomoki Watanabe, Paolo Favaro
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 Federated Deep AUC Maximization for Hetergeneous Data with a Constant Communication Complexity
Zhuoning Yuan, Zhishuai Guo, Yi Xu, Yiming Ying, Tianbao Yang
Poster
Tue 21:00 AutoAttend: Automated Attention Representation Search
Chaoyu Guan, Xin Wang, wenwu zhu
Poster
Tue 21:00 The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression
Florian List
Poster
Tue 21:00 Explore Visual Concept Formation for Image Classification
Shengzhou Xiong, Yihua Tan, Guoyou Wang
Poster
Tue 21:00 Data Augmentation for Meta-Learning
Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein
Poster
Tue 21:00 High-Performance Large-Scale Image Recognition Without Normalization
Andy Brock, Soham De, Samuel Smith, Karen Simonyan
Oral
Wed 5:00 Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky
Spotlight
Wed 5:20 SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Puru Kar, Manik Varma
Spotlight
Wed 5:25 Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
Ankit Singh Rawat, Aditya Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix Xinnan Yu, Sashank Jakkam Reddi, Sanjiv Kumar
Spotlight
Wed 5:35 Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification
Yu Bai, Song Mei, Huan Wang, Caiming Xiong
Spotlight
Wed 5:45 Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
Maria Refinetti, Sebastian Goldt, FLORENT KRZAKALA, Lenka Zdeborova
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
Oral
Wed 6:00 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Spencer Frei, Yuan Cao, Quanquan Gu
Oral
Wed 6:00 Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, CHEN Chen, Evangelos Theodorou
Spotlight
Wed 6:40 Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
Difan Zou, Spencer Frei, Quanquan Gu
Spotlight
Wed 6:45 Narrow Margins: Classification, Margins and Fat Tails
Francois Buet-Golfouse
Oral
Wed 7:00 PAC-Learning for Strategic Classification
Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao
Spotlight
Wed 7:25 A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel Robinson, Enrique Mallada, Rene Vidal
Spotlight
Wed 7:25 Deep Continuous Networks
Nergis Tomen, Silvia-Laura Pintea, Jan van Gemert
Spotlight
Wed 7:30 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold
Wenkai Xu, Takeru Matsuda
Spotlight
Wed 7:35 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori Ebihara
Spotlight
Wed 7:35 Active Deep Probabilistic Subsampling
Hans van Gorp, Iris Huijben, Bastiaan Veeling, Nicola Pezzotti, Ruud J. G. van Sloun
Spotlight
Wed 7:40 On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification
Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu
Spotlight
Wed 7:45 Learning Stochastic Behaviour from Aggregate Data
Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou
Poster
Wed 9:00 A Nullspace Property for Subspace-Preserving Recovery
Mustafa D Kaba, Chong You, Daniel Robinson, Enrique Mallada, Rene Vidal
Poster
Wed 9:00 PAC-Learning for Strategic Classification
Ravi Sundaram, Anil Vullikanti, Haifeng Xu, Fan Yao
Poster
Wed 9:00 Deep Continuous Networks
Nergis Tomen, Silvia-Laura Pintea, Jan van Gemert
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 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 Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
Difan Zou, Spencer Frei, Quanquan Gu
Poster
Wed 9:00 Learning Stochastic Behaviour from Aggregate Data
Shaojun Ma, Shu Liu, Hongyuan Zha, Haomin Zhou
Poster
Wed 9:00 Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
Spencer Frei, Yuan Cao, Quanquan Gu
Poster
Wed 9:00 Dynamic Game Theoretic Neural Optimizer
Guan-Horng Liu, CHEN Chen, Evangelos Theodorou
Poster
Wed 9:00 SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Puru Kar, Manik Varma
Poster
Wed 9:00 The Power of Log-Sum-Exp: Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
Taiki Miyagawa, Akinori Ebihara
Poster
Wed 9:00 Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed
Maria Refinetti, Sebastian Goldt, FLORENT KRZAKALA, Lenka Zdeborova
Poster
Wed 9:00 Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
Ankit Singh Rawat, Aditya Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix Xinnan Yu, Sashank Jakkam Reddi, Sanjiv Kumar
Poster
Wed 9:00 On-Off Center-Surround Receptive Fields for Accurate and Robust Image Classification
Zahra Babaiee, Ramin Hasani, Mathias Lechner, Daniela Rus, Radu Grosu
Poster
Wed 9:00 Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification
Yu Bai, Song Mei, Huan Wang, Caiming Xiong
Poster
Wed 9:00 Robust Density Estimation from Batches: The Best Things in Life are (Nearly) Free
Ayush Jain, Alon Orlitsky
Poster
Wed 9:00 Interpretable Stein Goodness-of-fit Tests on Riemannian Manifold
Wenkai Xu, Takeru Matsuda
Poster
Wed 9:00 Narrow Margins: Classification, Margins and Fat Tails
Francois Buet-Golfouse
Affinity Workshop
Wed 9:25 Breakout Session 2.8: Decision-Making in Social Settings: Addressing Strategic Feedback Effects
Oral
Wed 17:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Spotlight
Wed 17:20 Alternative Microfoundations for Strategic Classification
Meena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt
Spotlight
Wed 17:30 Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo
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 17:45 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 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Spotlight
Wed 18:25 Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel Hill, Inderjit Dhillon
Spotlight
Wed 18:25 An Information-Geometric Distance on the Space of Tasks
Yansong Gao, Pratik Chaudhari
Spotlight
Wed 18:30 Learning Deep Neural Networks under Agnostic Corrupted Supervision
Boyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou
Spotlight
Wed 18:35 Sample Complexity of Robust Linear Classification on Separated Data
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri
Spotlight
Wed 18:40 The Impact of Record Linkage on Learning from Feature Partitioned Data
Richard Nock, Stephen J Hardy, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne
Spotlight
Wed 18:45 Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
Oral
Wed 19:00 Multi-Dimensional Classification via Sparse Label Encoding
BINBIN JIA, Min-Ling Zhang
Spotlight
Wed 19:05 Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji
Spotlight
Wed 19:20 Lower-Bounded Proper Losses for Weakly Supervised Classification
Shuhei M Yoshida, Takashi Takenouchi, Masashi Sugiyama
Spotlight
Wed 19:25 SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun
Spotlight
Wed 19:25 Deep Learning for Functional Data Analysis with Adaptive Basis Layers
Junwen Yao, Jonas Mueller, Jane-Ling Wang
Spotlight
Wed 19:30 An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng, Kai-Wei Chang
Spotlight
Wed 19:35 Classification with Rejection Based on Cost-sensitive Classification
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
Spotlight
Wed 19:35 Exact Optimization of Conformal Predictors via Incremental and Decremental Learning
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
Spotlight
Wed 19:40 Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling
Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan Kumar Yadav
Spotlight
Wed 19:45 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Bagnell, Steven Wu
Poster
Wed 21:00 Top-k eXtreme Contextual Bandits with Arm Hierarchy
Rajat Sen, Alexander Rakhlin, Lexing Ying, Rahul Kidambi, Dean Foster, Daniel Hill, Inderjit Dhillon
Poster
Wed 21:00 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Bagnell, Steven Wu
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 An Integer Linear Programming Framework for Mining Constraints from Data
Tao Meng, Kai-Wei Chang
Poster
Wed 21:00 Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Mahdi Milani Fard, Sanmi Koyejo
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 An Information-Geometric Distance on the Space of Tasks
Yansong Gao, Pratik Chaudhari
Poster
Wed 21:00 Multi-Dimensional Classification via Sparse Label Encoding
BINBIN JIA, Min-Ling Zhang
Poster
Wed 21:00 Alternative Microfoundations for Strategic Classification
Meena Jagadeesan, Celestine Mendler-Dünner, Moritz Hardt
Poster
Wed 21:00 Label Distribution Learning Machine
Jing Wang, Xin Geng
Poster
Wed 21:00 Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang, Xin Gao, Xiangyang Ji
Poster
Wed 21:00 Lower-Bounded Proper Losses for Weakly Supervised Classification
Shuhei M Yoshida, Takashi Takenouchi, Masashi Sugiyama
Poster
Wed 21:00 The Impact of Record Linkage on Learning from Feature Partitioned Data
Richard Nock, Stephen J Hardy, Wilko Henecka, Hamish Ivey-Law, Jakub Nabaglo, Giorgio Patrini, Guillaume Smith, Brian Thorne
Poster
Wed 21:00 SagaNet: A Small Sample Gated Network for Pediatric Cancer Diagnosis
Yuhan Liu, Shiliang Sun
Poster
Wed 21:00 Learning Deep Neural Networks under Agnostic Corrupted Supervision
Boyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou
Poster
Wed 21:00 Classification with Rejection Based on Cost-sensitive Classification
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
Poster
Wed 21:00 Sample Complexity of Robust Linear Classification on Separated Data
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri
Poster
Wed 21:00 Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Poster
Wed 21:00 Massively Parallel and Asynchronous Tsetlin Machine Architecture Supporting Almost Constant-Time Scaling
Kuruge Darshana Abeyrathna, Bimal Bhattarai, Morten Goodwin, Saeed Rahimi Gorji, Ole-Christoffer Granmo, Lei Jiao, Rupsa Saha, Rohan Kumar Yadav
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 Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
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
Spotlight
Thu 5:20 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Spotlight
Thu 5:20 Dataset Condensation with Differentiable Siamese Augmentation
Bo Zhao, Hakan Bilen
Spotlight
Thu 5:25 Local Correlation Clustering with Asymmetric Classification Errors
Jafar Jafarov, Sanchit Kalhan, Kostya Makarychev, Yury Makarychev
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 5:35 SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V Bonilla, Theo Damoulas, Terry Lyons
Spotlight
Thu 5:35 A Collective Learning Framework to Boost GNN Expressiveness for Node Classification
Mengyue Hang, Jennifer Neville, Bruno Ribeiro
Spotlight
Thu 5:40 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Spotlight
Thu 5:45 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
Spotlight
Thu 5:45 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
Oral
Thu 6:00 Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
Yivan Zhang, Gang Niu, Masashi Sugiyama
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 6:35 Robust Representation Learning via Perceptual Similarity Metrics
Saeid A Taghanaki, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal
Spotlight
Thu 6:35 Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Spotlight
Thu 6:40 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
Spotlight
Thu 6:40 Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Kai Sheng Tai, Peter Bailis, Gregory Valiant
Spotlight
Thu 6:40 Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ikko Yamane, Junya Honda, Florian YGER, Masashi Sugiyama
Spotlight
Thu 6:45 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong
Spotlight
Thu 6:45 Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks
Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan
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 Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar, Li Jing, Ishan Misra, yann lecun, Stephane Deny
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 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
Spotlight
Thu 7:25 Pointwise Binary Classification with Pairwise Confidence Comparisons
Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
Spotlight
Thu 7:25 Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
Spotlight
Thu 7:25 Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Spotlight
Thu 7:30 Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama
Spotlight
Thu 7:35 SGLB: Stochastic Gradient Langevin Boosting
Aleksei Ustimenko, Liudmila Prokhorenkova
Spotlight
Thu 7:40 Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
Spotlight
Thu 7:45 Learning a Universal Template for Few-shot Dataset Generalization
Eleni Triantafillou, Hugo Larochelle, Richard Zemel, Vincent Dumoulin
Poster
Thu 9:00 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Poster
Thu 9:00 Dataset Condensation with Differentiable Siamese Augmentation
Bo Zhao, Hakan Bilen
Poster
Thu 9:00 Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Poster
Thu 9:00 Adversarial Robustness Guarantees for Random Deep Neural Networks
Giacomo De Palma, Bobak T Kiani, Seth Lloyd
Poster
Thu 9:00 SGLB: Stochastic Gradient Langevin Boosting
Aleksei Ustimenko, Liudmila Prokhorenkova
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 Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
Poster
Thu 9:00 Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Poster
Thu 9:00 Unified Robust Semi-Supervised Variational Autoencoder
Xu Chen
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 Local Correlation Clustering with Asymmetric Classification Errors
Jafar Jafarov, Sanchit Kalhan, Kostya Makarychev, Yury Makarychev
Poster
Thu 9:00 Sinkhorn Label Allocation: Semi-Supervised Classification via Annealed Self-Training
Kai Sheng Tai, Peter Bailis, Gregory Valiant
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 Lower Bounds on Cross-Entropy Loss in the Presence of Test-time Adversaries
Arjun Nitin Bhagoji, Daniel Cullina, Vikash Sehwag, Prateek Mittal
Poster
Thu 9:00 Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences
Ikko Yamane, Junya Honda, Florian YGER, Masashi Sugiyama
Poster
Thu 9:00 Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
Poster
Thu 9:00 Exact Optimization of Conformal Predictors via Incremental and Decremental Learning
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
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 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
Poster
Thu 9:00 Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks
Xin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan
Poster
Thu 9:00 Pointwise Binary Classification with Pairwise Confidence Comparisons
Lei Feng, Senlin Shu, Nan Lu, Bo Han, Miao Xu, Gang Niu, Bo An, Masashi Sugiyama
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 Learning from Similarity-Confidence Data
Yuzhou Cao, Lei Feng, Yitian Xu, Bo An, Gang Niu, Masashi Sugiyama
Poster
Thu 9:00 Learning Interaction Kernels for Agent Systems on Riemannian Manifolds
Mauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong
Poster
Thu 9:00 Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization
Yivan Zhang, Gang Niu, Masashi Sugiyama
Poster
Thu 9:00 Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar, Li Jing, Ishan Misra, yann lecun, Stephane Deny
Poster
Thu 9:00 Wasserstein Distributional Normalization For Robust Distributional Certification of Noisy Labeled Data
Sung Woo Park, Junseok Kwon
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 Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer
Seungwon Lee, Sima Behpour, Eric Eaton
Poster
Thu 9:00 SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Maud Lemercier, Cristopher Salvi, Thomas Cass, Edwin V Bonilla, Theo Damoulas, Terry Lyons
Poster
Thu 9:00 Learning a Universal Template for Few-shot Dataset Generalization
Eleni Triantafillou, Hugo Larochelle, Richard Zemel, Vincent Dumoulin
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
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 17:30 Group Fisher Pruning for Practical Network Compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang
Spotlight
Thu 17:30 PopSkipJump: Decision-Based Attack for Probabilistic Classifiers
Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause
Spotlight
Thu 17:35 Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
Dong Hoon Lee, Sae-Young Chung
Spotlight
Thu 17:40 Improved Algorithms for Agnostic Pool-based Active Classification
Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson
Spotlight
Thu 17:45 LogME: Practical Assessment of Pre-trained Models for Transfer Learning
Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long
Spotlight
Thu 17:45 Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners
Elias Chaibub Neto
Spotlight
Thu 17:45 Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees
Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen Bach, Eli Upfal
Oral
Thu 18:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Spotlight
Thu 18:20 Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification
Bo Pang, Ying Nian Wu
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 Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, Jose Alvarez
Spotlight
Thu 18:40 Supervised Tree-Wasserstein Distance
Yuki Takezawa, Ryoma Sato, Makoto Yamada
Spotlight
Thu 18:40 Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
Haoxiang Wang, Han Zhao, Bo Li
Oral
Thu 19:00 Learning Transferable Visual Models From Natural Language Supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever
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
Oral
Thu 19:00 A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
Spotlight
Thu 19:20 Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew Li, Tianyi Peng
Spotlight
Thu 19:20 Towards Defending against Adversarial Examples via Attack-Invariant Features
Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao
Spotlight
Thu 19:20 Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
Taehyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph Lim, Byoung-Tak Zhang
Spotlight
Thu 19:25 Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko
Spotlight
Thu 19:25 Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
Spotlight
Thu 19:35 HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections
Ines Chami, Albert Gu, Dat P Nguyen, Christopher Re
Spotlight
Thu 19:35 Improving Gradient Regularization using Complex-Valued Neural Networks
Eric Yeats, Yiran Chen, Hai Li
Spotlight
Thu 20:35 Fast margin maximization via dual acceleration
Ziwei Ji, Nati Srebro, Matus Telgarsky
Spotlight
Thu 20:35 Meta-Cal: Well-controlled Post-hoc Calibration by Ranking
Xingchen Ma, Matthew B Blaschko
Spotlight
Thu 20:40 Permutation Weighting
David Arbour, Drew Dimmery, Arjun Sondhi
Spotlight
Thu 20:45 Overcoming Catastrophic Forgetting by Bayesian Generative Regularization
Patrick Chen Chen, Wei Wei, Cho-Jui Hsieh, Bo Dai
Spotlight
Thu 20:50 Locally Adaptive Label Smoothing Improves Predictive Churn
Dara Bahri, Heinrich Jiang
Spotlight
Thu 20:50 Accelerating Gossip SGD with Periodic Global Averaging
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
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 Supervised Tree-Wasserstein Distance
Yuki Takezawa, Ryoma Sato, Makoto Yamada
Poster
Thu 21:00 A General Framework For Detecting Anomalous Inputs to DNN Classifiers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
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 Improved Algorithms for Agnostic Pool-based Active Classification
Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson
Poster
Thu 21:00 Group Fisher Pruning for Practical Network Compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, Wayne Zhang
Poster
Thu 21:00 Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
Poster
Thu 21:00 Meta-Cal: Well-controlled Post-hoc Calibration by Ranking
Xingchen Ma, Matthew B Blaschko
Poster
Thu 21:00 Unsupervised Embedding Adaptation via Early-Stage Feature Reconstruction for Few-Shot Classification
Dong Hoon Lee, Sae-Young Chung
Poster
Thu 21:00 Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners
Elias Chaibub Neto
Poster
Thu 21:00 Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees
Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen Bach, Eli Upfal
Poster
Thu 21:00 Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection
Nadine Chang, Zhiding Yu, Yu-Xiong Wang, Anima Anandkumar, Sanja Fidler, Jose Alvarez
Poster
Thu 21:00 PopSkipJump: Decision-Based Attack for Probabilistic Classifiers
Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause
Poster
Thu 21:00 Fast margin maximization via dual acceleration
Ziwei Ji, Nati Srebro, Matus Telgarsky
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 Unsupervised Part Representation by Flow Capsules
Sara Sabour Rouh Aghdam, Andrea Tagliasacchi, Soroosh Yazdani, Geoffrey Hinton, David Fleet
Poster
Thu 21:00 Learning Transferable Visual Models From Natural Language Supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever
Poster
Thu 21:00 Permutation Weighting
David Arbour, Drew Dimmery, Arjun Sondhi
Poster
Thu 21:00 Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
Haoxiang Wang, Han Zhao, Bo Li
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 Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
Taehyeong Kim, Injune Hwang, Hyundo Lee, Hyunseo Kim, Won-Seok Choi, Joseph Lim, Byoung-Tak Zhang
Poster
Thu 21:00 Latent Space Energy-Based Model of Symbol-Vector Coupling for Text Generation and Classification
Bo Pang, Ying Nian Wu
Poster
Thu 21:00 Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Vivek Farias, Andrew Li, Tianyi Peng
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 HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections
Ines Chami, Albert Gu, Dat P Nguyen, Christopher Re
Poster
Thu 21:00 Improving Gradient Regularization using Complex-Valued Neural Networks
Eric Yeats, Yiran Chen, Hai Li
Poster
Thu 21:00 Locally Adaptive Label Smoothing Improves Predictive Churn
Dara Bahri, Heinrich Jiang
Poster
Thu 21:00 Accelerating Gossip SGD with Periodic Global Averaging
Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
Poster
Thu 21:00 Object Segmentation Without Labels with Large-Scale Generative Models
Andrey Voynov, Stanislav Morozov, Artem Babenko
Poster
Thu 21:00 Towards Defending against Adversarial Examples via Attack-Invariant Features
Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao
Poster
Thu 21:00 Unsupervised Representation Learning via Neural Activation Coding
Yookoon Park, Sangho Lee, Gunhee Kim, David Blei
Poster
Thu 21:00 LogME: Practical Assessment of Pre-trained Models for Transfer Learning
Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long
Workshop
Fri 7:10 Have the Cake and Eat It Too? Higher Accuracy and Less Expense when Using Multi-label ML APIs Online
Lingjiao Chen
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
Sat 6:30 On the Fairness of Causal Algorithmic Recourse
Workshop
Sat 7:50 Self-Supervised Learning for Reasoning and Perception
Pengtao Xie, Shanghang Zhang, Ishan Misra, Pulkit Agrawal, Katerina Fragkiadaki, Ruisi Zhang, Tassilo Klein, Asli Celikyilmaz, Mihaela van der Schaar, Eric Xing
Workshop
Sat 9:15 Few-Shot Conformal Prediction with Auxiliary Tasks (Spotlight #1)
Adam Fisch
Workshop
Sat 9:33 Nested Conformal Prediction Sets for Classification with Applications to Probation Data (Spotlight #3)
Richard Berk
Workshop
Sat 11:45 Morning Poster Session: Prediction-Constrained Hidden Markov Models for Semi-Supervised Classification
Gabriel Hope
Workshop
Sat 12:30 Overparametrization: Insights from solvable models
Lenka Zdeborova
Workshop
Sat 12:37 Coresets for Classification – Simplified and Strengthened
Anup Rao, Tung Mai, Cameron Musco
Workshop
Sat 13:30 Contributed Talk #9
Keji Han
Workshop
Sat 15:35 Statistical Measures For Defining Curriculum Scoring Function
Vinu Sankar Sadasivan, Anirban Dasgupta
Workshop
Sat 15:40 An Extreme Point Approach to Subset Selection
Viveck Cadambe, Bill Kay
Workshop
Sat 15:50 SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios
Suraj N Kothawade, Krishnateja Killamsetty, Rishabh Lyer
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
Sat 16:24 Top-label calibration (Spotlight #7)
Chirag Gupta
Workshop
Sat 17:00 Afternoon Poster Session: DAMA-Net: A Novel Predictive Model for Irregularly Asynchronously andSparsely Sampled Multivariate Time Series
zhen wang
Workshop
Sat 18:03 Exact Optimization of Conformal Predictors via Incremental and Decremental Learning (Spotlight #13)
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
Workshop
Attacking Graph Classification via Bayesian Optimisation
Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A Osborne, Xiaowen Dong
Workshop
Adversarially Robust Learning via Entropic Regularization
Gauri Jagatap, Ameya Joshi, Animesh Chowdhury, Siddharth Garg, Chinmay Hegde
Workshop
Detecting AutoAttack Perturbations in the Frequency Domain
Peter Lorenz, Paula Harder, Dominik Straßel, Margret Keuper, Janis Keuper
Workshop
Defending Adversaries Using Unsupervised Feature Clustering VAE
Cheng Zhang, Pan Gao
Workshop
A Closer Look at the Adversarial Robustness of Information Bottleneck Models
Iryna Korshunova, David Stutz, Alex Alemi, Olivia Wiles, Sven Gowal
Workshop
Meta Adversarial Training against Universal Patches
Jan Hendrik Metzen, Nicole Finnie, Robin Hutmacher
Workshop
Query-based Adversarial Attacks on Graph with Fake Nodes
Zhengyi Wang, Zhongkai Hao, Jun Zhu
Workshop
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks
Lucie Charlotte Magister, Dmitry Kazhdan, Vikash Singh, Pietro Lió
Workshop
Severity Classification of Mental Health Related Tweets
Workshop
DFUQ poster 1 -- Distribution Free UQ for Classification Under Label Shift
Workshop
Counterfactual Explanations for Arbitrary Regression Models
Thomas Spooner, Danial Dervovic, Jon Shepard, Jiahao Chen, Daniele Magazzeni
Workshop
On the Fairness of Causal Algorithmic Recourse
Julius von Kügelgen, Amir Karimi, Umang Bhatt, Isabel Valera, Adrian Weller, Bernhard Schölkopf, Amir-Hossein Karimi
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
Increasing Depth Leads to U-Shaped Test Risk in Over-parameterized Convolutional Networks
Eshaan Nichani, Adit Radhakrishnan, Caroline Uhler
Workshop
Benign Overfitting in Adversarially Robust Linear Classification
Jinghui Chen, Yuan Cao, Yuan Cao, Quanquan Gu
Workshop
Label Noise SGD Provably Prefers Flat Global Minimizers
Alex Damian, Tengyu Ma, Jason Lee
Workshop
Benign Overfitting in Multiclass Classification: All Roads Lead to Interpolation
Ke Wang, Vidya Muthukumar, Christos Thrampoulidis
Workshop
Classification and Adversarial Examples in an Overparameterized Linear Model: A Signal-Processing Perspective
Adhyyan Narang, Vidya Muthukumar, Anant Sahai
Workshop
Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks
Shih-Yu Sun, Vimal Thilak, Etai Littwin, Omid Saremi, Josh M Susskind
Workshop
Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures
Yuan Cao, Yuan Cao, Quanquan Gu, Mikhail Belkin
Workshop
Over-Parameterization and Generalization in Audio Classification
Khaled Koutini, Khaled Koutini, Hamid Eghbalzadeh, Florian Henkel, Jan Schlüter, Gerhard Widmer
Workshop
Binary Classification of Gaussian Mixtures: Abundance of Support Vectors, Benign Overfitting and Regularization
Ke Wang, Christos Thrampoulidis
Workshop
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini, Orestis Paraskevas, Samet Oymak, Christos Thrampoulidis
Workshop
Early-stopped neural networks are consistent
Ziwei Ji, Matus Telgarsky
Workshop
Distribution-free uncertainty quantification for classification under label shift
Workshop
On Misclassification-Aware Smoothing for Robustness and Uncertainty Calibration
Workshop
PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation
Workshop
An Analysis of the Deployment of Models Trained on Private Tabular Synthetic Data: Unexpected Surprises
Mayana Wanderley Pereira, Rahul Dodhia, Juan Lavista Ferres
Workshop
SNoB: Social Norm Bias of “Fair” Algorithms
Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
Workshop
A Standardized Data Collection Toolkit for Model Benchmarking
Avanika Narayan, Piero Molino, Karan Goel, Christopher Re
Workshop
FlyNN: Fruit-fly Inspired Federated Nearest Neighbor Classification
Workshop
Federated Graph Classification over Non-IID Graphs
Workshop
Differentially Private Classification via 0-1 Loss
Ryan McKenna
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
Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff
Mitch Naylor
Workshop
Using Associative Classification and Odds Ratios for In-Hospital Mortality Risk Estimation
Oliver Haas, Andreas Maier, Eva Rothgang
Workshop
Tree-based local explanations of machine learning model predictions – AraucanaXAI
Enea Parimbelli, Giovanna Nicora, Szymon Wilk, Wojtek Michalowski, Riccardo Bellazzi
Workshop
A reject option for automated sleep stage scoring
Dries Van der Plas, Wannes Meert, Jesse Davis
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
An Interpretable Algorithm for Uveal Melanoma Subtyping from Whole Slide Cytology Images
Haomin Chen, Alvin Liu, Catalina Gomez, Zelia Correa, Mathias Unberath
Workshop
Variable selection via the sum of single effect neural networks with credible sets
Wei Cheng, Sohini Ramachandran, Lorin Crawford
Workshop
Fast Hierarchical Games for Image Explanations
Jacopo Teneggi, Alexandre Luster, jsulam Sulam
Workshop
Have the Cake and Eat It Too? Higher Accuracy and Less Expense when Using Multi-label ML APIs Online
Lingjiao Chen, James Zou, Matei Zaharia
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
FERMI: Fair Empirical Risk Minimization Via Exponential Rényi Mutual Information
Andrew Lowy, Rakesh Pavan, Sina Baharlouei, Meisam Razaviyayn, Ahmad Beirami
Workshop
Robust Counterfactual Explanations for Privacy-Preserving SVM
Rami Mochaourab, Panagiotis Papapetrou
Workshop
Are You Man Enough? Even Fair Algorithms Conform to Societal Norms
Myra Cheng, Maria De-Arteaga, Lester Mackey, Adam Tauman Kalai
Workshop
CrossWalk: Fairness-enhanced Node Representation Learning
Ahmad Khajehnejad, Moein Khajehnejad, Krishna Gummadi, Adrian Weller, Baharan Mirzasoleiman
Workshop
Statistical Guarantees for Fairness Aware Plug-In Algorithms
Drona Khurana, Srinivasan Ravichandran, Sparsh Jain, Narayanan Edakunni
Workshop
Representation Learning for Out-of-distribution Generalization in Downstream Tasks
Frederik Träuble, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter V Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
Workshop
Immuno-mimetic Deep Neural Networks (Immuno-Net)
Ren Wang
Workshop
MultImp: Multiomics Generative Models for Data Imputation
Yining Jiao
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
Graph attribution methods applied to understanding immunogenicity in glycans
Somesh M Mohapatra
Workshop
Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, J. Bagnell, Steven Wu
Workshop
Representation Learning for Out-of-distribution Generalization in Downstream Tasks
Frederik Träuble, Andrea Dittadi, Manuel Wüthrich, Felix Widmaier, Peter Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, Stefan Bauer
Workshop
SIMILAR: Submodular Information Measures Based Active Learning In Realistic Scenarios
Suraj N Kothawade, Krishnateja Killamsetty, Rishabh Lyer
Workshop
An Interpretable Algorithm for Uveal Melanoma Subtyping from Whole Slide Cytology Images
Haomin Chen, Alvin Liu, Catalina Gomez, Zelia Correa, Mathias Unberath
Workshop
Variable selection via the sum of single effect neural networks with credible sets
Wei Cheng, Sohini Ramachandran, Lorin Crawford
Workshop
Fast Hierarchical Games for Image Explanations
Jacopo Teneggi, Alexandre Luster, jsulam Sulam
Workshop
IADA: Iterative Adversarial Data Augmentation Using Formal Verification and Expert Guidance
Ruixuan Liu, Changliu Liu
Workshop
High Frequency EEG Artifact Detection with Uncertainty via Early Exit Paradigm
Lorena Qendro, Alex Campbell, Pietro Lió, Cecilia Mascolo
Workshop
Coresets for Classification – Simplified and Strengthened
Anup Rao, Tung Mai, Cameron Musco
Workshop
Statistical Measures For Defining Curriculum Scoring Function
Vinu Sankar Sadasivan, Anirban Dasgupta
Workshop
An Extreme Point Approach to Subset Selection
Viveck Cadambe, Bill Kay
Workshop
Hierarchical Multiple-Instance Data Classification with Costly Features
Jaromír Janisch, Tomas Pevny, Viliam Lisy
Workshop
Effective Evaluation of Deep Active Learning on Image Classification Tasks
Nathan Beck, Durga S, Ganesh Ramakrishnan, Rishabh Lyer
Workshop
Urban Tree Species Classification Using Aerial Imagery
Mahdi Maktabdar Oghaz
Workshop
BERT Classification of Paris Agreement Climate Action Plans
Tom Corringham
Workshop
Challenges in Applying Audio Classification Models to Datasets Containing Crucial Biodiversity Information
Jacob Ayers
Workshop
ForestViT: A Vision Transformer Network for Convolution-free Multi-label Image Classification in Deforestation Analysis
Athanasios Voulodimos
Workshop
Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap
Gokul Swamy, Sanjiban Choudhury, Drew Bagnell, Steven Wu
Workshop
Using Anomaly Feature Vectors for Detecting, Classifying and Warning of Outlier Adversarial Examples
Nelson Manohar-Alers, Ryan Feng, Sahib Singh, Jiguo Song, Atul Prakash
Workshop
Attacking Few-Shot Classifiers with Adversarial Support Poisoning
Elre Oldewage, John Bronskill, Richard E Turner
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
Detecting Adversarial Examples Is (Nearly) As Hard As Classifying Them
Florian Tramer
Workshop
Self-Supervised Iterative Contextual Smoothing for Efficient Adversarial Defense against Gray- and Black-Box Attack
Sungmin Cha, Naeun Ko, YoungJoon Yoo, Taesup Moon
Workshop
Membership Inference Attacks on Lottery Ticket Networks
Aadesh Bagmar, Shishira Maiya, Shruti Bidwalkar, Amol Deshpande
Workshop
The Interplay between Distribution Parameters and the Accuracy-Robustness Tradeoff in Classification
Seyed Alireza Mousavi Hosseini, Amir None Abouei, Mohammad H Rohban
Workshop
Disrupting Model Training with Adversarial Shortcuts
Aditya Kusupati, Tadayoshi Kohno, Ivan Evtimov, Ian Covert
Workshop
Less is More: Feature Selection for Adversarial Robustness with Compressive Counter-Adversarial Attacks
Emre Ozfatura, Muhammad Zaid Hameed, Kerem Ozfatura, Deniz Gunduz
Workshop
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
Duhun Hwang, Eunjung Lee, Wonjong Rhee
Workshop
Is It Time to Redefine the Classification Task for Deep Learning Systems?
Keji Han, Yun Li, Songcan Chen
Workshop
Certified robustness against adversarial patch attacks via randomized cropping
Wan-Yi Lin, Fatemeh Sheikholeslami, jinghao shi, Leslie Rice, Zico Kolter