论文标题
Softsort：Argsort操作员的连续放松
SoftSort: A Continuous Relaxation for the argsort Operator
论文作者
论文摘要
虽然排序是计算机科学中的一个重要过程，但Argsort操作员（将其作为输入矢量并返回其排序排列量）具有离散的图像，因此几乎到处都有零梯度。这禁止端到端，基于梯度的学习依赖Argsort操作员的模型。克服这个问题的自然方法是通过连续放松代替Argsort操作员。最近的工作显示了许多方法，但是到目前为止提出的放松在计算上是复杂的。在这项工作中，我们为Argsort操作员提出了一个简单的持续放松，具有以下质量：它可以以三行代码（实现最新的性能实现）实现，很容易在数学上进行推理 - 实质上简化了证明 - 比竞争方法更快。我们开源代码以复制所有实验和结果。
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.
