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Expo Workshop
Sun 5:00 Real World RL: Azure Personalizer & Vowpal Wabbit
Sheetal Lahabar, Etienne Kintzler, Mark Rucker, Bogdan Mazoure, Qingyun Wu, Pavithra Srinath, Jack Gerrits, Olga Vrousgou, John Langford, Eduardo Salinas
Expo Workshop
Sun 6:30 AutoML
Qingyun Wu, Qingyun Wu
Oral
Tue 5:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Chi-Chun Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Spotlight
Tue 21:20 AutoSampling: Search for Effective Data Sampling Schedules
MING SUN, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui
Spotlight
Tue 5:25 Explainable Automated Graph Representation Learning with Hyperparameter Importance
Xin Wang, Shuyi Fan, Kun Kuang, wenwu zhu
Spotlight
Tue 21:25 HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik
Oral Session
Tue 6:00 AutoML and Deep Architecture
Spotlight
Tue 22:20 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
Oral Session
Tue 7:00 AutoML and Neural Network Architectures 1
Poster
Tue 9:00 BORE: Bayesian Optimization by Density-Ratio Estimation
Louis Chi-Chun Tiao, Aaron Klein, Matthias W Seeger, Edwin V Bonilla, Cedric Archambeau, Fabio Ramos
Poster
Wed 1:00 HardCoRe-NAS: Hard Constrained diffeRentiable Neural Architecture Search
Niv Nayman, Yonathan Aflalo, Asaf Noy, Lihi Zelnik
Poster
Wed 1:00 AutoSampling: Search for Effective Data Sampling Schedules
MING SUN, Haoxuan Dou, Baopu Li, Junjie Yan, Wanli Ouyang, Lei Cui
Poster
Wed 1:00 Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius, Heng Wang, Lorenzo Torresani
Poster
Tue 9:00 Explainable Automated Graph Representation Learning with Hyperparameter Importance
Xin Wang, Shuyi Fan, Kun Kuang, wenwu zhu
Oral
Tue 17:00 CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
Spotlight
Tue 17:40 High Confidence Generalization for Reinforcement Learning
James Kostas, Yash Chandak, Scott Jordan, Georgios Theocharous, Philip Thomas
Spotlight
Tue 18:00 iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Ehsan Abbasnejad, Reza Haffari
Spotlight Session
Tue 18:00 AutoML
Spotlight
Tue 18:05 Accurate Post Training Quantization With Small Calibration Sets
Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry
Spotlight
Tue 18:10 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search
Vu Nguyen, Tam Le, Makoto Yamada, Michael A Osborne
Oral
Tue 18:15 Few-Shot Neural Architecture Search
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Spotlight
Tue 18:35 AutoAttend: Automated Attention Representation Search
Chaoyu Guan, Xin Wang, wenwu zhu
Spotlight
Tue 18:40 Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
Xingchen Wan, Vu Nguyen, Huong Ha, Binxin Ru, Cong Lu, Michael A Osborne
Spotlight
Tue 18:45 Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin
Oral Session
Tue 19:00 AutoML and Neural Network Architectures 2
Poster
Tue 21:00 Accurate Post Training Quantization With Small Calibration Sets
Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, Daniel Soudry
Poster
Tue 21:00 CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu, Mi Zhang
Poster
Tue 21:00 High Confidence Generalization for Reinforcement Learning
James Kostas, Yash Chandak, Scott Jordan, Georgios Theocharous, Philip Thomas
Poster
Tue 21:00 iDARTS: Differentiable Architecture Search with Stochastic Implicit Gradients
Miao Zhang, Steven Su, Shirui Pan, Xiaojun Chang, Ehsan Abbasnejad, Reza Haffari
Poster
Tue 21:00 Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search
Vu Nguyen, Tam Le, Makoto Yamada, Michael A Osborne
Poster
Tue 21:00 Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
Yonggan Fu, Yongan Zhang, Yang Zhang, David Cox, Yingyan Lin
Poster
Tue 21:00 Few-Shot Neural Architecture Search
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Poster
Tue 21:00 Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces
Xingchen Wan, Vu Nguyen, Huong Ha, Binxin Ru, Cong Lu, Michael A Osborne
Poster
Tue 21:00 AutoAttend: Automated Attention Representation Search
Chaoyu Guan, Xin Wang, wenwu zhu
Spotlight
Wed 6:40 ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
Poster
Wed 9:00 ChaCha for Online AutoML
Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
Spotlight
Thu 11:25 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Spotlight
Thu 11:30 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Poster
Thu 13:00 AdaXpert: Adapting Neural Architecture for Growing Data
Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
Poster
Thu 13:00 Quantile Bandits for Best Arms Identification
Mengyan Zhang, Cheng Soon Ong
Spotlight
Thu 19:20 A Scalable Deterministic Global Optimization Algorithm for Clustering Problems
Kaixun Hua, Mingfei Shi, Yankai Cao
Poster
Thu 21:00 A Scalable Deterministic Global Optimization Algorithm for Clustering Problems
Kaixun Hua, Mingfei Shi, Yankai Cao
Workshop
Fri 6:00 8th ICML Workshop on Automated Machine Learning (AutoML 2021)
Gresa Shala, Frank Hutter, Joaquin Vanschoren, Marius Lindauer, Katharina Eggensperger, Colin White, Erin LeDell
Workshop
Fri 6:06 Invited Talk by Matthias Feurer: Towards hands-free AutoML
Matthias Feurer
Workshop
Fri 7:25 A resource-efficient method for repeated HPO and NAS problems
Workshop
Fri 7:26 Latency-Aware Neural Architecture Search with Multi-Objective Bayesian Optimization
David Eriksson
Workshop
Fri 7:27 GPy-ABCD: A Configurable Automatic Bayesian Covariance Discovery Implementation
Thomas Fletcher
Workshop
Fri 7:28 Bandit Limited Discrepancy Search and Application to Machine Learning Pipeline Optimization
Akihiro Kishimoto
Workshop
Fri 7:29 Towards Model Selection using Learning Curve Cross-Validation
Jan N. van Rijn
Workshop
Fri 23:30 Dynamic Pruning of a Neural Network via Gradient Signal-to-Noise Ratio
Julien Siems
Workshop
Fri 7:31 AutoML Adoption in ML Software
Koen van der Blom
Workshop
Fri 7:32 Leveraging Theoretical Tradeoffs in Hyperparameter Selection for Improved Empirical Performance
Parikshit Ram
Workshop
Fri 7:33 Bag of Baselines for Multi-objective Joint Neural Architecture Search and Hyperparameter Optimization
Thomas Elsken, Difan Deng
Workshop
Fri 7:35 Towards Explaining Hyperparameter Optimization via Partial Dependence Plots
Julia Moosbauer, Julia Herbinger
Workshop
Fri 23:36 Mutation is all you need
Lennart Schneider
Workshop
Fri 7:37 Meta Learning the Step Size in Policy Gradient Methods
Luca Sabbioni
Workshop
Fri 7:40 Poster Session #1
Workshop
Fri 9:00 Contributed Talk: Discovering Weight Initializers with Meta Learning
Dmitry Baranchuk
Workshop
Fri 9:15 Contributed Talk: Multimodal AutoML on Structured Tables with Text Fields
Jonas Mueller
Workshop
Fri 9:30 Contributed Talk: Automated Discovery of Adaptive Attacks on Adversarial Defenses
Chengyuan Yao
Workshop
Fri 9:45 Sequential Automated Machine Learning: Bandits-driven Exploration using a Collaborative Filtering Representation
Maxime Heuillet
Workshop
Fri 9:46 LRTuner: A Learning Rate Tuner for Deep Neural Networks
Nipun Kwatra
Workshop
Fri 9:47 PonderNet: Learning to Ponder
Andrea Banino
Workshop
Fri 9:48 Replacing the Ex-Def Baseline in AutoML by Naive AutoML
Felix Mohr
Workshop
Fri 9:49 Neural Fixed-Point Acceleration for Convex Optimization
Shobha Venkataraman
Workshop
Fri 9:50 Ranking Architectures by their Feature Extraction Capabilities
Debadeepta Dey
Workshop
Fri 9:51 Incorporating domain knowledge into neural-guided search via in situ priors and constraints
Mikel Landajuela Larma
Workshop
Sat 1:52 Tabular Data: Deep Learning is Not All You Need
Ravid Shwartz-Ziv
Workshop
Sat 1:53 Automated Learning Rate Scheduler for Large-batch Training
Chiheon Kim
Workshop
Fri 9:54 Adaptation-Agnostic Meta-Training
Jiaxin Chen
Workshop
Fri 9:55 On-the-fly learning of adaptive strategies with bandit algorithms
Rashid Bakirov
Workshop
Fri 9:56 Poster Session #2
Workshop
Fri 11:01 Invited Talk by Kim Montgomery: Bias, Controlling Bias, and AutoML
Kim Montgomery
Workshop
AutoML Adoption in ML Software
Koen van der Blom, Alex Serban, Holger Hoos, Joost Visser
Workshop
Replacing the Ex-Def Baseline in AutoML by Naive AutoML
Felix Mohr, Marcel Wever
Workshop
Towards Model Selection using Learning Curve Cross-Validation
Felix Mohr, Jan N Rijn
Workshop
Multimodal AutoML on Structured Tables with Text Fields
Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alex Smola
Workshop
Tabular Data: Deep Learning is Not All You Need
Ravid Shwartz-Ziv, Amitai Armon
Workshop
Incorporating domain knowledge into neural-guided search via in situ priors and constraints
Brenden Petersen, Claudio Santiago, Mikel Landajuela Larma
Workshop
Neural Fixed-Point Acceleration for Convex Optimization
Shobha Venkataraman, Brandon Amos
Workshop
Sequential Automated Machine Learning: Bandits-driven Exploration using a Collaborative Filtering Representation
Maxime Heuillet, Benoit Debaque, Audrey Durand