Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

Large Scale ◽

Deep Neural Networks ◽

High Dimensional Data ◽

Particle Swarm ◽

Parameter Selection ◽

High Dimensional ◽

Swarm Optimization ◽

Selection For

Proceedings of the Genetic and Evolutionary Computation Conference Companion on - GECCO '17 ◽

Hyper-parameter selection in deep neural networks using parallel particle swarm optimization

10.1145/3067695.3084211 ◽

2017 ◽

Cited By ~ 19

Author(s):

Pablo Ribalta Lorenzo ◽

Jakub Nalepa ◽

Luciano Sanchez Ramos ◽

José Ranilla Pastor

Keyword(s):

Neural Networks ◽

Parallel Particle Swarm Optimization

Deep Neural Networks ◽

Particle Swarm ◽

Parameter Selection ◽

Swarm Optimization ◽

Proceedings of the Genetic and Evolutionary Computation Conference on - GECCO '17 ◽

Particle swarm optimization for hyper-parameter selection in deep neural networks

10.1145/3071178.3071208 ◽

2017 ◽

Cited By ~ 33

Author(s):

Pablo Ribalta Lorenzo ◽

Jakub Nalepa ◽

Michal Kawulok ◽

Luciano Sanchez Ramos ◽

José Ranilla Pastor

Keyword(s):

Neural Networks ◽

Deep Neural Networks ◽

Particle Swarm ◽

Parameter Selection ◽

Convergence and Spectral Radius Analysis and Parameter Selection for the Particle Swarm Optimization Algorithm Based on the Stochastic Process

Information Technology Journal ◽

10.3923/itj.2013.1480.1490 ◽

2013 ◽

Vol 12 (8) ◽

pp. 1480-1490

Author(s):

Long-Hua Ma ◽

Ming Xu ◽

Meng Shao ◽

Zhe-Ming Lu

Keyword(s):

Stochastic Process ◽

Spectral Radius ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Particle Swarm ◽

Parameter Selection ◽

Swarm Optimization ◽

Selection For

A Crow Particle Swarm Optimization Algorithm with Deep Neural Network (CPSO-DNN) for High Dimensional Data Analysis

2020 International Conference on Communication and Signal Processing (ICCSP) ◽

10.1109/iccsp48568.2020.9182181 ◽

2020 ◽

Author(s):

Bibhuprasad Sahu ◽

Amrutanshu Panigrahi ◽

Sasmita Pani ◽

Shrabanee Swagatika ◽

Debabrata Singh ◽

...

Keyword(s):

Neural Network ◽

Data Analysis ◽

Optimization Algorithm ◽

Deep Neural Network ◽

Particle Swarm Optimization Algorithm ◽

High Dimensional Data ◽

Particle Swarm ◽

High Dimensional ◽

Finding relevant clustering directions in high-dimensional data using Particle Swarm Optimization

Journal of Chemometrics ◽

10.1002/cem.1345 ◽

2010 ◽

Vol 25 (7) ◽

pp. 366-374 ◽

Cited By ~ 6

Author(s):

Federico Marini ◽

Beata Walczak

Keyword(s):

High Dimensional Data ◽

Particle Swarm ◽

High Dimensional ◽

Parameter selection for particle swarm optimization based on Stochastic multi-objective optimization

2015 Chinese Automation Congress (CAC) ◽

10.1109/cac.2015.7382846 ◽

2015 ◽

Cited By ~ 3

Author(s):

Ming Xu ◽

JiangPing Gu

Keyword(s):

Particle Swarm ◽

Parameter Selection ◽

Multi Objective Optimization ◽

Swarm Optimization ◽

Multi Objective ◽

Selection For

Cognitive Deep Neural Networks prediction method for software fault tendency module based on Bound Particle Swarm Optimization

Cognitive Systems Research ◽

10.1016/j.cogsys.2018.06.001 ◽

2018 ◽

Vol 52 ◽

pp. 12-20 ◽

Cited By ~ 8

Author(s):

Wang Geng

Keyword(s):

Neural Networks ◽

Deep Neural Networks ◽

Particle Swarm ◽

Prediction Method ◽

Swarm Optimization ◽

Software Fault

PSO-PS:Parameter Synchronization with Particle Swarm Optimization for Distributed Training of Deep Neural Networks

2020 International Joint Conference on Neural Networks (IJCNN) ◽

10.1109/ijcnn48605.2020.9207698 ◽

2020 ◽

Author(s):

Qing Ye ◽

Yuxuan Han ◽

Yanan Sun ◽

Jiancheng Lv

Keyword(s):

Neural Networks ◽

Deep Neural Networks ◽

Particle Swarm ◽

Swarm Optimization ◽

Distributed Training

Feature Selection of High Dimensional Data by Adaptive Potential Particle Swarm Optimization

2019 IEEE Congress on Evolutionary Computation (CEC) ◽

10.1109/cec.2019.8790366 ◽

2019 ◽

Cited By ~ 3

Author(s):

Xingyue Huang ◽

Yizhou Chi ◽

Yu Zhou

Keyword(s):

Feature Selection ◽

High Dimensional Data ◽

Particle Swarm ◽

High Dimensional ◽

Adaptive Potential ◽

Swarm Optimization ◽

Selection Of

A Novel Hybrid Analog Design Optimizer with Particle Swarm Optimization and modern Deep Neural Networks

2019 International SoC Design Conference (ISOCC) ◽

10.1109/isocc47750.2019.9027647 ◽

2019 ◽

Author(s):

Ahmed Elsiginy ◽

Mohamed Elmahdy ◽

Eman Azab

Keyword(s):

Neural Networks ◽

Deep Neural Networks ◽

Particle Swarm ◽

Analog Design ◽