Model Performance Scaling with Multiple Data Sources
ICML 2021 | July 2021
July 18, 2021 –
July 24, 2021
Microsoft at ICML 2021
位置: Virtual
出版物
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Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
-
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
2021 International Conference on Machine Learning | July 2021
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UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang
2021 International Conference on Machine Learning | July 2021
-
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
2021 International Conference on Machine Learning | July 2021
-
Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
2021 International Conference on Machine Learning | July 2021
-
Statistical Estimation from Dependent Data
Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis
2021 International Conference on Machine Learning | July 2021
-
SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Purushottam Kar, Manik Varma
ICML 2021 | July 2021
-
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
2021 International Conference on Machine Learning | July 2021
-
Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
2021 International Conference on Machine Learning | July 2021
-
Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
2021 International Conference on Machine Learning | July 2021
-
Poolingformer: Long Document Modeling with Pooling Attention
Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Wei Chen
2021 International Conference on Machine Learning | July 2021
-
Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021 International Conference on Machine Learning | July 2021
-
On the Problem of Underranking in Group-Fair Ranking
Sruthi Gorantla, Amit Deshpande, Anand Louis
2021 International Conference on Machine Learning | July 2021
-
Off-Policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
2021 International Conference on Machine Learning | July 2021
-
Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul Gopal Krishnan, David Sontag
2021 International Conference on Machine Learning | July 2021
-
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
2021 International Conference on Machine Learning | May 2021
-
Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos, Paul Grigas, Zheng Wen
2021 International Conference on Machine Learning | April 2021
-
Interactive Learning from Activity Description
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miro Dudík, Patrick Shafto
2021 International Conference on Machine Learning | July 2021
-
Interaction-Grounded Learning
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
2021 International Conference on Machine Learning | July 2021
-
Integrated Defense for Resilient Graph Matching
Jiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou, Yelong Shen
ICML 2021 | July 2021
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Incentivizing Compliance with Algorithmic Instruments
Dung Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu
2021 International Conference on Machine Learning | July 2021
-
How could Neural Networks understand Programs
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
2021 International Conference on Machine Learning | March 2021
-
Finding k in Latent k-polytope
Chiranjib Bhattacharyya, Ravi Kannan, Amit Kumar
2021 International Conference on Machine Learning | July 2021
-
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021 International Conference on Machine Learning | July 2021
-
Exploiting structured data for learning contagious diseases under incomplete testing
Maggie Makar, Lauren R West, David C Hooper, Eric Horvitz, Erica Shenoy, John Guttag
2021 International Conference on Machine Learning | May 2021
-
Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2021 International Conference on Machine Learning | July 2021
-
EL-Attention: Memory Efficient Lossless Attention for Generation
Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang
2021 International Conference on Machine Learning | July 2021
-
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet des Combes
2021 International Conference on Machine Learning | July 2021
-
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
-
Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin
2021 International Conference on Machine Learning | May 2021
-
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
-
Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
2021 International Conference on Machine Learning | July 2021
-
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Honglak Lee, Mehdi Fatemi
2021 International Conference on Machine Learning | May 2021
-
Correlation Clustering in Constant Many Parallel Rounds
Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski
2021 International Conference on Machine Learning | July 2021
-
Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
International Conference on Machine Learning | July 2021
-
Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
2021 International Conference on Machine Learning | July 2021
-
Adversarial Dueling Bandits
Aadirupa Saha, Tomer Koren, Yishay Mansour
International Conference on Machine Learning | July 2021
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
2021 International Conference on Machine Learning | May 2021
-
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
2021 International Conference on Machine Learning | July 2021
-
Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
編集者: Marina Meila and Tong Zhang
-
ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
2021 International Conference on Machine Learning (ICML 2021) | July 2021
-
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
2021 International Conference on Machine Learning (ICML) | July 2021
-
Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
-
Large Scale Private Learning via Low-rank Reparametrization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
International Conference on Machine Learning (ICML) | July 2021
-
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
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Differentially Private Correlation Clustering
Mark Bun, Marek Eliás, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | February 2021
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Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size
Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak
2021 International Conference on Machine Learning (ICML 2021) | July 2021
-
Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward J. Hu
ICML 2021 | May 2021
-
-
-
BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Dayiheng Liu, Wei Chen, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan
2021 International Conference on Machine Learning | December 2020
-
-
-
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
2021 International Conference on Machine Learning | May 2021
-
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
2021 International Conference on Machine Learning | March 2021
-
Correlation Clustering in Constant Many Parallel Rounds
Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski
2021 International Conference on Machine Learning | July 2021
-
Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
International Conference on Machine Learning | July 2021
-
Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
2021 International Conference on Machine Learning | July 2021
-
Adversarial Dueling Bandits
Aadirupa Saha, Tomer Koren, Yishay Mansour
International Conference on Machine Learning | July 2021
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
2021 International Conference on Machine Learning (ICML 2021) | July 2021
-
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
2021 International Conference on Machine Learning (ICML) | July 2021
-
Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
-
Differentially Private Correlation Clustering
Mark Bun, Marek Eliás, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | February 2021
-
-
-
Model Performance Scaling with Multiple Data Sources
ICML 2021 | July 2021
-
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
-
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
2021 International Conference on Machine Learning | July 2021
-
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang
2021 International Conference on Machine Learning | July 2021
-
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
2021 International Conference on Machine Learning | July 2021
-
Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
2021 International Conference on Machine Learning | July 2021
-
Statistical Estimation from Dependent Data
Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis
2021 International Conference on Machine Learning | July 2021
-
SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Purushottam Kar, Manik Varma
ICML 2021 | July 2021
-
Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
2021 International Conference on Machine Learning | July 2021
-
Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
2021 International Conference on Machine Learning | July 2021
-
Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
2021 International Conference on Machine Learning | July 2021
-
Poolingformer: Long Document Modeling with Pooling Attention
Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Wei Chen
2021 International Conference on Machine Learning | July 2021
-
Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021 International Conference on Machine Learning | July 2021
-
On the Problem of Underranking in Group-Fair Ranking
Sruthi Gorantla, Amit Deshpande, Anand Louis
2021 International Conference on Machine Learning | July 2021
-
Off-Policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
2021 International Conference on Machine Learning | July 2021
-
Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul Gopal Krishnan, David Sontag
2021 International Conference on Machine Learning | July 2021
-
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
2021 International Conference on Machine Learning | May 2021
-
Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos, Paul Grigas, Zheng Wen
2021 International Conference on Machine Learning | April 2021
-
Interactive Learning from Activity Description
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miro Dudík, Patrick Shafto
2021 International Conference on Machine Learning | July 2021
-
Interaction-Grounded Learning
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
2021 International Conference on Machine Learning | July 2021
-
Integrated Defense for Resilient Graph Matching
Jiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou, Yelong Shen
ICML 2021 | July 2021
-
Incentivizing Compliance with Algorithmic Instruments
Dung Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu
2021 International Conference on Machine Learning | July 2021
-
How could Neural Networks understand Programs
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
2021 International Conference on Machine Learning | March 2021
-
Finding k in Latent k-polytope
Chiranjib Bhattacharyya, Ravi Kannan, Amit Kumar
2021 International Conference on Machine Learning | July 2021
-
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021 International Conference on Machine Learning | July 2021
-
Exploiting structured data for learning contagious diseases under incomplete testing
Maggie Makar, Lauren R West, David C Hooper, Eric Horvitz, Erica Shenoy, John Guttag
2021 International Conference on Machine Learning | May 2021
-
Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2021 International Conference on Machine Learning | July 2021
-
EL-Attention: Memory Efficient Lossless Attention for Generation
Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang
2021 International Conference on Machine Learning | July 2021
-
Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet des Combes
2021 International Conference on Machine Learning | July 2021
-
Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
-
BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Dayiheng Liu, Wei Chen, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan
2021 International Conference on Machine Learning | December 2020
-
Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin
2021 International Conference on Machine Learning | May 2021
-
Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
-
Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
2021 International Conference on Machine Learning | July 2021
-
Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Honglak Lee, Mehdi Fatemi
2021 International Conference on Machine Learning | May 2021
-
Correlation Clustering in Constant Many Parallel Rounds
Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski
2021 International Conference on Machine Learning | July 2021
-
Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
International Conference on Machine Learning | July 2021
-
Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
2021 International Conference on Machine Learning | July 2021
-
Adversarial Dueling Bandits
Aadirupa Saha, Tomer Koren, Yishay Mansour
International Conference on Machine Learning | July 2021
-
Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
-
The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
2021 International Conference on Machine Learning | May 2021
-
Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
2021 International Conference on Machine Learning | July 2021
-
Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
編集者: Marina Meila and Tong Zhang
-
ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
2021 International Conference on Machine Learning (ICML 2021) | July 2021
-
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
2021 International Conference on Machine Learning (ICML) | July 2021
-
Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
-
Large Scale Private Learning via Low-rank Reparametrization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
International Conference on Machine Learning (ICML) | July 2021
-
Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
-
Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size
Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak
2021 International Conference on Machine Learning (ICML 2021) | July 2021
-
Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward J. Hu
ICML 2021 | May 2021
-
-
-
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
-
-
-
Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
2021 International Conference on Machine Learning (ICML) | July 2021
-
Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
-
-
-
UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang
2021 International Conference on Machine Learning | July 2021
-
How could Neural Networks understand Programs
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2021 International Conference on Machine Learning | July 2021
-
-
-
Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
2021 International Conference on Machine Learning | July 2021
-
Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward J. Hu
ICML 2021 | May 2021
-
-
-
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
-
Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul Gopal Krishnan, David Sontag
2021 International Conference on Machine Learning | July 2021
-
-
-
How could Neural Networks understand Programs
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
-
-
-
Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
2021 International Conference on Machine Learning | July 2021
-
-
-
Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
編集者: Marina Meila and Tong Zhang
-
Large Scale Private Learning via Low-rank Reparametrization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
International Conference on Machine Learning (ICML) | July 2021
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Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size
Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak
2021 International Conference on Machine Learning (ICML 2021) | July 2021
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Model Performance Scaling with Multiple Data Sources
ICML 2021 | July 2021
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Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs
Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel Coelho de Castro
ICML 2021 Workshop on Interpretable Machine Learning in Healthcare | July 2021
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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
2021 International Conference on Machine Learning | July 2021
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UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data
Chengyi Wang, Yu Wu, Yao Qian, Kenichi Kumatani, Shujie Liu, Furu Wei, Michael Zeng, Xuedong Huang
2021 International Conference on Machine Learning | July 2021
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Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
2021 International Conference on Machine Learning | July 2021
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Temporally Correlated Task Scheduling for Sequence Learning
Xueqing Wu, Lewen Wang, Yingce Xia, Weiqing Liu, Lijun Wu, Shufang Xie, Tao Qin, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
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TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL
Clément Romac, Rémy Portelas, Katja Hofmann, Pierre-Yves Oudeyer
2021 International Conference on Machine Learning | July 2021
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Statistical Estimation from Dependent Data
Vardis Kandiros, Yuval Dagan, Nishanth Dikkala, Surbhi Goel, Constantinos Daskalakis
2021 International Conference on Machine Learning | July 2021
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SiameseXML: Siamese Networks meet Extreme Classifiers with 100M Labels
Kunal Dahiya, Ananye Agarwal, Deepak Saini, Gururaj K, Jian Jiao, Amit Singh, Sumeet Agarwal, Purushottam Kar, Manik Varma
ICML 2021 | July 2021
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Scalable Variational Gaussian Processes via Harmonic Kernel Decomposition
Shengyang Sun, Jiaxin Shi, Andrew Wilson, Roger Grosse
2021 International Conference on Machine Learning | July 2021
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Quantum algorithms for reinforcement learning with a generative model
Daochen Wang, Aarthi Sundaram, Robin Kothari, Ashish Kapoor, Martin Roetteler
2021 International Conference on Machine Learning | July 2021
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Provably Correct Optimization and Exploration with Non-linear Policies
Fei Feng, Wotao Yin, Alekh Agarwal, Lin Yang
2021 International Conference on Machine Learning | July 2021
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Poolingformer: Long Document Modeling with Pooling Attention
Hang Zhang, Yeyun Gong, Yelong Shen, Weisheng Li, Jiancheng Lv, Nan Duan, Wei Chen
2021 International Conference on Machine Learning | July 2021
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Online Learning with Optimism and Delay
Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey
2021 International Conference on Machine Learning | July 2021
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On the Problem of Underranking in Group-Fair Ranking
Sruthi Gorantla, Amit Deshpande, Anand Louis
2021 International Conference on Machine Learning | July 2021
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Off-Policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
2021 International Conference on Machine Learning | July 2021
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Neural Pharmacodynamic State Space Modeling
Zeshan Hussain, Rahul Gopal Krishnan, David Sontag
2021 International Conference on Machine Learning | July 2021
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Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Hou
2021 International Conference on Machine Learning | May 2021
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Joint Online Learning and Decision-making via Dual Mirror Descent
Alfonso Lobos, Paul Grigas, Zheng Wen
2021 International Conference on Machine Learning | April 2021
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Interactive Learning from Activity Description
Khanh Nguyen, Dipendra Misra, Robert E. Schapire, Miro Dudík, Patrick Shafto
2021 International Conference on Machine Learning | July 2021
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Interaction-Grounded Learning
Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
2021 International Conference on Machine Learning | July 2021
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Integrated Defense for Resilient Graph Matching
Jiaxiang Ren, Zijie Zhang, Jiayin Jin, Xin Zhao, Sixing Wu, Yang Zhou, Yelong Shen, Tianshi Che, Ruoming Jin, Dejing Dou, Yelong Shen
ICML 2021 | July 2021
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Incentivizing Compliance with Algorithmic Instruments
Dung Ngo, Logan Stapleton, Vasilis Syrgkanis, Steven Wu
2021 International Conference on Machine Learning | July 2021
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How could Neural Networks understand Programs
Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
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Graph Neural Networks Inspired by Classical Iterative Algorithms
Yongyi Yang, Tang Liu, Yangkun Wang, Jinjing Zhou, Quan Gan, Zhewei Wei, Zheng Zhang, Zengfeng Huang, David Wipf
2021 International Conference on Machine Learning | March 2021
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Finding k in Latent k-polytope
Chiranjib Bhattacharyya, Ravi Kannan, Amit Kumar
2021 International Conference on Machine Learning | July 2021
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Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
Luisa Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021 International Conference on Machine Learning | July 2021
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Exploiting structured data for learning contagious diseases under incomplete testing
Maggie Makar, Lauren R West, David C Hooper, Eric Horvitz, Erica Shenoy, John Guttag
2021 International Conference on Machine Learning | May 2021
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Evolving Attention with Residual Convolutions
Yujing Wang, Yaming Yang, Jiangang Bai, Mingliang Zhang, Jing Bai, Jing Yu, Ce Zhang, Gao Huang, Yunhai Tong
2021 International Conference on Machine Learning | July 2021
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EL-Attention: Memory Efficient Lossless Attention for Generation
Yu Yan, Jiusheng Chen, Weizhen Qi, Nikhil Bhendawade, Yeyun Gong, Nan Duan, Ruofei Zhang
2021 International Conference on Machine Learning | July 2021
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Decomposed Mutual Information Estimation for Contrastive Representation Learning
Alessandro Sordoni, Nouha Dziri, Hannes Schulz, Geoff Gordon, Philip Bachman, Remi Tachet des Combes
2021 International Conference on Machine Learning | July 2021
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Dataset Dynamics via Gradient Flows in Probability Space
David Alvarez-Melis, Nicolo Fusi
ICML 2021 | July 2021
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BANG: Bridging Autoregressive and Non-autoregressive Generation with Large Scale Pretraining
Weizhen Qi, Yeyun Gong, Jian Jiao, Yu Yan, Dayiheng Liu, Wei Chen, Kewen Tang, Houqiang Li, Jiusheng Chen, Ruofei Zhang, Ming Zhou, Nan Duan
2021 International Conference on Machine Learning | December 2020
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Tensor Programs IIb: Architectural Universality Of Neural Tangent Kernel Training Dynamics
Greg Yang, Etai Littwin
2021 International Conference on Machine Learning | May 2021
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Accuracy, Interpretability, and Differential Privacy via Explainable Boosting
Harsha Nori, Rich Caruana, Zhiqi Bu, Judy Hanwen Shen, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | July 2021
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Acceleration via Fractal Learning Rate Schedules
Naman Agarwal, Surbhi Goel, Cyril Zhang
2021 International Conference on Machine Learning | July 2021
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Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks
Sungryull Sohn, Sungtae Lee, Jongwook Choi, Harm van Seijen, Honglak Lee, Mehdi Fatemi
2021 International Conference on Machine Learning | May 2021
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Correlation Clustering in Constant Many Parallel Rounds
Vincent Cohen-Addad, Silvio Lattanzi, Slobodan Mitrović, Ashkan Norouzi-Fard, Nikos Parotsidis, Jakub Tarnawski
2021 International Conference on Machine Learning | July 2021
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Confidence-Budget Matching for Sequential Budgeted Learning
Yonathan Efroni, Nadav Merlis, Aadirupa Saha, Shie Mannor
International Conference on Machine Learning | July 2021
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Optimal Regret Algorithm for Pseudo-1d Bandit Convex Optimization
Aadirupa Saha, Nagarajan Natarajan, Praneeth Netrapalli, Prateek Jain
2021 International Conference on Machine Learning | July 2021
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Adversarial Dueling Bandits
Aadirupa Saha, Tomer Koren, Yishay Mansour
International Conference on Machine Learning | July 2021
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Domain Generalization using Causal Matching
Divyat Mahajan, Shruti Tople, Amit Sharma
International Conference on Machine Learning (ICML) | July 2021
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The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu
2021 International Conference on Machine Learning | July 2021
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GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
2021 International Conference on Machine Learning | May 2021
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Safe Reinforcement Learning Using Advantage-Based Intervention
Nolan Wagener, Byron Boots, Ching-An Cheng
2021 International Conference on Machine Learning | July 2021
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Grey-box Extraction of Natural Language Models
Santiago Zanella-Béguelin, Shruti Tople, Andrew Paverd, Boris Köpf
International Conference on Machine Learning | July 2021
編集者: Marina Meila and Tong Zhang
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ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
2021 International Conference on Machine Learning (ICML 2021) | July 2021
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Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
2021 International Conference on Machine Learning (ICML) | July 2021
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Network Inference and Influence Maximization from Samples
Wei Chen, Xiaoming Sun, Jialin Zhang, Zhijie Zhang
2021 International Conference on Machine Learning (ICML) | July 2021
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Large Scale Private Learning via Low-rank Reparametrization
Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
International Conference on Machine Learning (ICML) | July 2021
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Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation
Sam Devlin, Raluca Stevenson, Ida Momennejad, Jaroslaw Rzepecki, Evelyn Zuniga, Gavin Costello, Guy Leroy, Ali Shaw, Katja Hofmann
2021 International Conference on Machine Learning | July 2021
Source code available at: https://github.com/microsoft/NTT
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Differentially Private Correlation Clustering
Mark Bun, Marek Eliás, Janardhan (Jana) Kulkarni
2021 International Conference on Machine Learning | February 2021
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Boosting the Throughput and Accelerator Utilization of Specialized CNN Inference Beyond Increasing Batch Size
Jack Kosaian, Amar Phanishayee, Matthai Philipose, Debadeepta Dey, Rashmi Vinayak
2021 International Conference on Machine Learning (ICML 2021) | July 2021
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Tensor Programs IV: Feature Learning in Infinite-Width Neural Networks
Greg Yang, Edward J. Hu
ICML 2021 | May 2021
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