Instead of Rewriting Foreign Code for Machine Learning, Automatically Synthesize Fast Gradients

1 code implementation • NeurIPS 2020 • William S. Moses, Valentin Churavy

Applying differentiable programming techniques and machine learning algorithms to foreign programs requires developers to either rewrite their code in a machine learning framework, or otherwise provide derivatives of the foreign code.

BIG-bench Machine Learning

Extracting Incentives from Black-Box Decisions

no code implementations • 13 Oct 2019 • Yonadav Shavit, William S. Moses

An algorithmic decision-maker incentivizes people to act in certain ways to receive better decisions.

Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions

4 code implementations • 13 Feb 2018 • Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, Priya Goyal, Zachary DeVito, William S. Moses, Sven Verdoolaege, Andrew Adams, Albert Cohen

Deep learning models with convolutional and recurrent networks are now ubiquitous and analyze massive amounts of audio, image, video, text and graph data, with applications in automatic translation, speech-to-text, scene understanding, ranking user preferences, ad placement, etc.

BIG-bench Machine Learning Management +2