RL based hyper-parameters optimization algorithm (ROA) for convolutional neural network
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
RL based hyper-parameters optimization algorithm (ROA) for convolutional neural network
Authors
Keywords
-
Journal
Journal of Ambient Intelligence and Humanized Computing
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-03-19
DOI
10.1007/s12652-022-03788-y
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A Comprehensive Survey of Neural Architecture Search
- (2021) Pengzhen Ren et al. ACM COMPUTING SURVEYS
- A Survey of Deep RL and IL for Autonomous Driving Policy Learning
- (2021) Zeyu Zhu et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- ZeroNAS: Differentiable Generative Adversarial Networks Search for Zero-Shot Learning
- (2021) Caixia Yan et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Weighted Random Search for CNN Hyperparameter Optimization
- (2020) Razvan Andonie et al. International Journal of Computers Communications & Control
- Deep learning in environmental remote sensing: Achievements and challenges
- (2020) Qiangqiang Yuan et al. REMOTE SENSING OF ENVIRONMENT
- Deep learning on image denoising: An overview
- (2020) Chunwei Tian et al. NEURAL NETWORKS
- An optimal artificial neural network based big data application for heart disease diagnosis and classification model
- (2020) R. Thanga Selvi et al. Journal of Ambient Intelligence and Humanized Computing
- Deep Top-$k$ Ranking for Image–Sentence Matching
- (2019) Lingling Zhang et al. IEEE TRANSACTIONS ON MULTIMEDIA
- Dynamic Affinity Graph Construction for Spectral Clustering Using Multiple Features
- (2018) Zhihui Li et al. IEEE Transactions on Neural Networks and Learning Systems
- Rank-Constrained Spectral Clustering With Flexible Embedding
- (2018) Zhihui Li et al. IEEE Transactions on Neural Networks and Learning Systems
- Adaptive Unsupervised Feature Selection With Structure Regularization
- (2018) Minnan Luo et al. IEEE Transactions on Neural Networks and Learning Systems
- An Adaptive Semisupervised Feature Analysis for Video Semantic Recognition
- (2018) Minnan Luo et al. IEEE Transactions on Cybernetics
- Adaptive Semi-Supervised Feature Selection for Cross-Modal Retrieval
- (2018) En Yu et al. IEEE TRANSACTIONS ON MULTIMEDIA
- Sparse, collaborative, or nonnegative representation: Which helps pattern classification?
- (2018) Jun Xu et al. PATTERN RECOGNITION
- Ten quick tips for machine learning in computational biology
- (2017) Davide Chicco BioData Mining
- Compound Rank- $k$ Projections for Bilinear Analysis
- (2016) Xiaojun Chang et al. IEEE Transactions on Neural Networks and Learning Systems
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now