Hierarchical Collaborative Hyper-parameter Tuning. (arXiv:2205.05272v1 [cs.LG])

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

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 …

arxiv collaborative hierarchical