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)
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
Christopher Joseph Maddison
David Duvenaud
Will Grathwohl
ICML (2021)
A Hierarchical Neural Model of Data Prefetching
Zhan Shi
Akanksha Jain
Calvin Lin
Architectural Support for Programming Languages and Operating Systems (ASPLOS) (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)
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)
Learned Hardware/Software Co-Design of Neural Accelerators
Zhan Shi
Chirag Sakhuja
Calvin Lin
ML for Systems Workshop at NeurIPS 2020 (2020)
