Kevin Swersky
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Data-Driven Offline Optimization for Architecting Hardware Accelerators
Aviral Kumar
Sergey Levine
International Conference on Learning Representations 2022 (to appear)
A Hierarchical Neural Model of Data Prefetching
Zhan Shi
Akanksha Jain
Calvin Lin
Architectural Support for Programming Languages and Operating Systems (ASPLOS) (2021)
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Christopher Joseph Maddison
David Duvenaud
Will Grathwohl
ICML (2021)
Big Self-Supervised Models are Strong Semi-Supervised Learners
Ting Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey Everest Hinton
Advances in Neural Information Processing Systems (2020)
An Imitation Learning Approach for Cache Replacement
Evan Z. Liu
International Conference on Machine Learning (2020)
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples
Eleni Triantafillou
Tyler Zhu
Kelvin Xu
Carles Gelada
Hugo Larochelle
International Conference on Learning Representations (submission) (2020)
Optimizing Long-term Social Welfare in Recommender Systems:A Constrained Matching Approach
Martin Mladenov
Elliot Creager
Omer Ben-Porat
Richard Zemel
Proceedings of the Thirty-seventh International Conference on Machine Learning (ICML-20), Vienna, Austria (2020)
