198 citations · 481 across the 31 of their papers we have counts for
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cs.LG2021★ 2 cited
Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions
Todd Huster, Jeremy E. J. Cohen, Zinan Lin +5
Generative adversarial networks (GANs) are often billed as "universal distribution learners", but precisely what distributions they can represent and learn is still an open questio…
cs.PL2021★ 35 cited
MLGO: a Machine Learning Guided Compiler Optimizations Framework
Mircea Trofin, Yundi Qian, Eugene Brevdo +3
Leveraging machine-learning (ML) techniques for compiler optimizations has been widely studied and explored in academia. However, the adoption of ML in general-purpose, industry st…