Neural architecture search: a probabilistic approach

Show simple item record Lut, Volodymyr 2020-06-17T23:31:24Z 2020-06-17T23:31:24Z 2020
dc.identifier.citation Lut, Volodymyr. Neural architecture search: a probabilistic approach : Master Thesis : manuscript rights / Volodymyr Lut ; Supervisor Yuriy Khoma, Vasilii Ganishev ; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2020. – 27 p. : ill. uk
dc.language.iso en uk
dc.subject neural architecture uk
dc.subject probabilistic approach uk
dc.subject encoding uk
dc.title Neural architecture search: a probabilistic approach uk
dc.type Preprint uk
dc.status Публікується вперше uk
dc.description.abstracten In this project, we introduce the Bayesian Optimization (BO) implementation of the NAS algorithm that is exploiting patterns found in most optimal unique architectures sampled from the most popular NAS dataset and benchmarking tool NASbench-101 (Dong and Yang, 2020a). The proposed solution leverages a novel approach to path-encoding and is designed to perform reproducible search even on a relatively small initial batch obtained from the random search. This implementation does not require any special hardware, it is publicly available.

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