论文标题
在并行或分布式异步迭代中，具有无限延迟，可能出现订单消息或灵活的通信，以进行凸优化问题和机器学习
On Parallel or Distributed Asynchronous Iterations with Unbounded Delays and Possible Out of Order Messages or Flexible Communication for Convex Optimization Problems and Machine Learning
论文作者
论文摘要
我们描述了并行或分布式异步迭代算法的几个功能，例如无限延迟，可能的订单消息或灵活的通信。我们专注于宏观序列的概念，该序列是为了研究异步迭代的收敛或终止。还提出了对凸优化问题的异步迭代的调查。最后，提出了针对并行或分布的异步迭代算法的新结果，该算法具有灵活的通信，用于凸优化问题和机器学习。
We describe several features of parallel or distributed asynchronous iterative algorithms such as unbounded delays, possible out of order messages or flexible communication. We concentrate on the concept of macroiteration sequence which was introduced in order to study the convergence or termination of asynchronous iterations. A survey of asynchronous iterations for convex optimization problems is also presented. Finally, a new result of convergence for parallel or distributed asynchronous iterative algorithms with flexible communication for convex optimization problems and machine learning is proposed.
