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Affinity Workshop
Mon 10:30 Ceramic Cracks Segmentation with Deep Learning
Gerivan Junior, Janderson Ferreira, Cristian Millán, Ramiro Ruiz, Alberto Junior, Bruno Fernandes
Spotlight
Wed 19:45 A large-scale benchmark for few-shot program induction and synthesis
Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama, Tomas Lozano-Perez, Leslie Kaelbling, Josh Tenenbaum
Poster
Wed 21:00 A large-scale benchmark for few-shot program induction and synthesis
Ferran Alet, Javier Lopez-Contreras, James Koppel, Maxwell Nye, Armando Solar-Lezama, Tomas Lozano-Perez, Leslie Kaelbling, Josh Tenenbaum
Oral
Thu 5:00 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Spotlight
Thu 5:20 Dataset Condensation with Differentiable Siamese Augmentation
Bo Zhao, Hakan Bilen
Spotlight
Thu 5:25 PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause
Spotlight
Thu 5:30 Parameterless Transductive Feature Re-representation for Few-Shot Learning
Wentao Cui, Yuhong Guo
Spotlight
Thu 5:35 Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer
Seungwon Lee, Sima Behpour, Eric Eaton
Spotlight
Thu 5:40 Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Spotlight
Thu 5:45 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
Spotlight
Thu 6:40 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
Oral
Thu 7:00 Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
Spotlight
Thu 7:25 Representation Subspace Distance for Domain Adaptation Regression
Xinyang Chen, Sinan Wang, Jianmin Wang, Mingsheng Long
Spotlight
Thu 7:30 Personalized Federated Learning using Hypernetworks
Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik
Spotlight
Thu 7:35 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
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 Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
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 Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment
Michael Chang, Sid Kaushik, Sergey Levine, Thomas Griffiths
Poster
Thu 9:00 A Discriminative Technique for Multiple-Source Adaptation
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
Poster
Thu 9:00 Few-Shot Conformal Prediction with Auxiliary Tasks
Adam Fisch, Tal Schuster, Tommi Jaakkola, Regina Barzilay
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 Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao, Shiyu Chang, Regina Barzilay
Poster
Thu 9:00 Aggregating From Multiple Target-Shifted Sources
Changjian Shui, Zijian Li, Jiaqi Li, Christian Gagne, Charles X. Ling, Boyu Wang
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 Parameterless Transductive Feature Re-representation for Few-Shot Learning
Wentao Cui, Yuhong Guo
Poster
Thu 9:00 Personalized Federated Learning using Hypernetworks
Aviv Shamsian, Aviv Navon, Ethan Fetaya, Gal Chechik
Poster
Thu 9:00 PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause
Poster
Thu 9:00 f-Domain Adversarial Learning: Theory and Algorithms
David Acuna, Guojun Zhang, Marc Law, Sanja Fidler
Oral
Thu 17:00 Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization
Sang Michael Xie, Tengyu Ma, Percy Liang
Spotlight
Thu 17:20 KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
Haozhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen
Spotlight
Thu 17:25 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Spotlight
Thu 17:30 Exploiting Shared Representations for Personalized Federated Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
Spotlight
Thu 17:35 Large-Scale Meta-Learning with Continual Trajectory Shifting
JWoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang
Spotlight
Thu 17:40 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Max Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
Spotlight
Thu 17:45 LogME: Practical Assessment of Pre-trained Models for Transfer Learning
Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long
Oral
Thu 18:00 WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
Spotlight
Thu 18:20 Improving Generalization in Meta-learning via Task Augmentation
Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying WEI, Li Tian, James Zou, Junzhou Huang, Zhenhui (Jessie) Li
Spotlight
Thu 18:25 Improving Predictors via Combination Across Diverse Task Categories
Kwang In Kim
Spotlight
Thu 18:30 MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration
Jin Zhang, Jianhao Wang, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan, Chongjie Zhang
Spotlight
Thu 18:35 Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
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
Spotlight
Thu 19:25 A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
Nikunj Saunshi, Arushi Gupta, Wei Hu
Spotlight
Thu 19:30 Meta-Learning Bidirectional Update Rules
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas
Spotlight
Thu 19:35 Function Contrastive Learning of Transferable Meta-Representations
Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf
Spotlight
Thu 19:40 A Discriminative Technique for Multiple-Source Adaptation
Corinna Cortes, Mehryar Mohri, Ananda Theertha Suresh, Ningshan Zhang
Poster
Thu 21:00 WILDS: A Benchmark of in-the-Wild Distribution Shifts
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
Poster
Thu 21:00 Improving Predictors via Combination Across Diverse Task Categories
Kwang In Kim
Poster
Thu 21:00 MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration
Jin Zhang, Jianhao Wang, Hao Hu, Tong Chen, Yingfeng Chen, Changjie Fan, Chongjie Zhang
Poster
Thu 21:00 Meta-Learning Bidirectional Update Rules
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas
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 Improving Generalization in Meta-learning via Task Augmentation
Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying WEI, Li Tian, James Zou, Junzhou Huang, Zhenhui (Jessie) Li
Poster
Thu 21:00 KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
Haozhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen
Poster
Thu 21:00 Large-Scale Meta-Learning with Continual Trajectory Shifting
JWoong Shin, Hae Beom Lee, Boqing Gong, Sung Ju Hwang
Poster
Thu 21:00 REPAINT: Knowledge Transfer in Deep Reinforcement Learning
Yunzhe Tao, Sahika Genc, Jonathan Chung, TAO SUN, Sunil Mallya
Poster
Thu 21:00 A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
Nikunj Saunshi, Arushi Gupta, Wei Hu
Poster
Thu 21:00 Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization
Sang Michael Xie, Tengyu Ma, Percy Liang
Poster
Thu 21:00 Offline Meta-Reinforcement Learning with Advantage Weighting
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn
Poster
Thu 21:00 Function Contrastive Learning of Transferable Meta-Representations
Waleed Gondal, Shruti Joshi, Nasim Rahaman, Stefan Bauer, Manuel Wuthrich, Bernhard Schölkopf
Poster
Thu 21:00 Exploiting Shared Representations for Personalized Federated Learning
Liam Collins, Hamed Hassani, Aryan Mokhtari, Sanjay Shakkottai
Poster
Thu 21:00 LogME: Practical Assessment of Pre-trained Models for Transfer Learning
Kaichao You, Yong Liu, Jianmin Wang, Mingsheng Long
Poster
Thu 21:00 Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Max Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
Poster
Thu 21:00 Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation
Haoxiang Wang, Han Zhao, Bo Li
Workshop
When does loss-based prioritization fail?
Niel Hu, Xinyu Hu, Rosanne Liu, Sara Hooker, Jason Yosinski
Workshop
Mitigating deep double descent by concatenating inputs
John Chen, Qihan Wang, Tasos Kyrillidis
Workshop
Model Mis-specification and Algorithmic Bias
Yangfan Liang, Peter Zhang
Workshop
Soft BIBD and Product Gradient Codes: Coding Theoretic Constructions to Mitigate Stragglers in Distributed Learning
Animesh Sakorikar, Lele Wang