SoftSort：argsort算子的连续松弛
SoftSort: A Continuous Relaxation for the argsort Operator
摘要：
虽然排序是计算机科学中的一个重要过程，但argsort运算符--它接受一个向量作为输入并返回其排序排列--具有离散图像，因此几乎到处都是零梯度。这禁止了依赖argsort操作符的端到端的、基于梯度的模型学习。克服这个问题的一个自然的方法是用连续松弛代替argsort运算符。最近的工作已经显示了许多方法来做到这一点，但到目前为止提出的松弛计算是复杂的。在这项工作中，我们提出了一个简单的连续放松的argsort运算符，它具有以下品质：它可以在三行代码中实现，实现最先进的性能，很容易在数学上的原因-大大简化证明-并且比竞争方法更快。我们开放源代码来重现所有的实验和结果。
英文摘要：
While sorting is an important procedure in computer science, the argsort operator - which takes as input a vector and returns its sorting permutation - 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, but the relaxations proposed so far are computationally complex. In this work we propose a simple continuous relaxation for the argsort operator which has the following qualities: 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 faster than competing approaches. We open source the code to reproduce all of the experiments and results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
