SoftSort: A Continuous Relaxation for the argsort Operator

Jul 12, 2020



Sorting is an important procedure in computer science. However, the argsort operator - which takes as input a vector and returns its sorting per-mutation - has a discrete image and thus zero gradients almost everywhere. This prohibits end-to-end, gradient-based learning of models that rely on the argsort operator. A natural way to overcome this problem is to replace the argsort operator with a continuous relaxation. Recent work has shown a number of ways to do this. However, the relaxations proposed so far are computationally complex. In this work we propose a simple continuous relaxation for the argsort operator. Unlike previous works, our relaxation is straight-forward: it can be implemented in three lines of code, achieves state-of-the-art performance, is easy to reason about mathematically - substantially simplifying proofs - and is up to six times faster than competing approaches. We open-source the code to reproduce all of the experiments



About ICML 2020

The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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