Web: http://arxiv.org/abs/2205.05272

May 12, 2022, 1:11 a.m. | Ahmad Esmaeili, Zahra Ghorrati, Eric Matson

cs.LG updates on arXiv.org arxiv.org

Hyper-parameter Tuning is among the most critical stages in building machine
learning solutions. This paper demonstrates how multi-agent systems can be
utilized to develop a distributed technique for determining near-optimal values
for any arbitrary set of hyper-parameters in a machine learning model. The
proposed method employs a distributedly formed hierarchical agent-based
architecture for the cooperative searching procedure of tuning hyper-parameter
values. The presented generic model is used to develop a guided randomized
agent-based tuning technique, and its behavior is investigated …

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