Topics
Prospective authors are invited to submit papers on relevant theory and applications related, but not limited to, the following list of topics:
- Deep learning techniques
- Deep generative models
- Self-supervised and semi-supervised learning
- Adversarial machine learning
- Graph neural networks
- Learning from multimodal data
- Learning theory and algorithms
- Distributed/Federated learning
- Machine learning over wireless networks
- Reinforcement learning
- Matrix factorization/completion
- Dictionary learning
- Source separation
- Independent component analysis
- Sparsity-aware learning
- Tensor-based signal processing
- Information-theoretic learning
- Pattern recognition and classification
- Feature extraction/selection/learning
- Applications of machine learning
Papers should not be longer than 6 pages, including all text, figures and references, according to the Paper Submission Guidelines. All the accepted and presented papers will be published in and indexed by IEEE Xplore.
Important Dates
- April 28, 2023: Deadline for regular paper submissions
- July 3, 2023: Notification of paper acceptance
- July 17, 2023: Camera-ready upload