$L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning$

L $^{2}$ NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning

International Conference on Information and Knowledge Management (CIKM), 2021

25 September 2021

Mohammad Salameh

Seyed Saeed Changiz Rezaei

Wei Lu

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Papers citing "L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning"

5 / 5 papers shown

Title
An Integrated Approach to Neural Architecture Search for Deep Q-Networks Iman Rahmani Saman Yazdannik Morteza Tayefi Jafar Roshanian 17 0 0 22 Oct 2025
Dextr: Zero-Shot Neural Architecture Search with Singular Value Decomposition and Extrinsic Curvature Rohan Asthana Joschua Conrad M. Ortmanns Vasileios Belagiannis 52 0 0 18 Aug 2025
AIO-P: Expanding Neural Performance Predictors Beyond Image ClassificationAAAI Conference on Artificial Intelligence (AAAI), 2022 Keith G. Mills Di Niu Mohammad Salameh Weichen Qiu Fred X. Han Puyuan Liu Jialin Zhang Wei Lu Shangling Jui 175 7 0 30 Nov 2022
GENNAPE: Towards Generalized Neural Architecture Performance EstimatorsAAAI Conference on Artificial Intelligence (AAAI), 2022 Keith G. Mills Fred X. Han Jialin Zhang Fabián A. Chudak A. Mamaghani Mohammad Salameh Wei Lu Shangling Jui Di Niu 163 8 0 30 Nov 2022
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture SearchInternational Conference on Information and Knowledge Management (CIKM), 2022 Xinshun Feng Herun Wan Shangbin Feng Hongrui Wang Jun Zhou Qinghua Zheng Minnan Luo 118 6 0 18 Aug 2022

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