二元矩阵猜想问题
Binary Matrix Guessing Problem
摘要：
本文介绍了二元矩阵猜测问题，并给出了两种算法来解决这个问题。我们介绍的第一个算法是元素探测算法（EPA），它在利用Frobenius距离的分数下非常快。第二种算法是加性强化学习算法，它结合了感知器算法和强化学习算法的思想。该算法与第一个算法相比速度明显较慢，但限制较少，泛化能力更好。我们比较这两种算法的计算性能，并提供数值结果。撤回原因：论文将重写，并在经过验证和确认的硬件和软件上重复实验。
英文摘要：
We introduce the Binary Matrix Guessing Problem and provide two algorithms to solve this problem. The first algorithm we introduce is Elementwise Probing Algorithm (EPA) which is very fast under a score which utilizes Frobenius Distance. The second algorithm is Additive Reinforcement Learning Algorithm which combines ideas from perceptron algorithm and reinforcement learning algorithm. This algorithm is significantly slower compared to first one, but less restrictive and generalizes better. We compare computational performance of both algorithms and provide numerical results. reason for withdrawal: Paper will be rewritten with experiments replicated on verified and validated hardware and software.
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。
