论文标题
压缩和数据相似性：两种技术的结合，用于解决分布式变异不平等的沟通效率解决方案
Compression and Data Similarity: Combination of Two Techniques for Communication-Efficient Solving of Distributed Variational Inequalities
论文作者
论文摘要
变分不平等是一个重要的工具，包括最小化，马鞍，游戏，固定点问题。现代的大规模和计算昂贵的实用应用是解决这些问题流行的分布式方法。同时，大多数分布式系统都有基本问题 - 通信瓶颈。有各种各样的技术可以处理。特别是，在本文中，我们考虑了两种流行方法的组合：压缩和数据相似性。我们表明，这种协同作用比分别解决分布的平滑平滑单调变化不等式的每种方法更有效。实验证实了理论结论。
Variational inequalities are an important tool, which includes minimization, saddles, games, fixed-point problems. Modern large-scale and computationally expensive practical applications make distributed methods for solving these problems popular. Meanwhile, most distributed systems have a basic problem - a communication bottleneck. There are various techniques to deal with it. In particular, in this paper we consider a combination of two popular approaches: compression and data similarity. We show that this synergy can be more effective than each of the approaches separately in solving distributed smooth strongly monotone variational inequalities. Experiments confirm the theoretical conclusions.
