4th International Conference on Information Theory and Machine Learning (ITEORY 2026)
November 14 ~ 15, 2026, Melbourne, Australia
Scope & Topics
4th International Conference on Information Theory and Machine Learning (ITEORY 2026) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Information Theory. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the area soft Information Theory, Applications and Machine Learning.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Computer Science, Engineering and Applications.
Topics of interest include, but are not limited to, the following
- Shannon Theory and Fundamental Limits
- Finite Blocklength and High Dimensional Information Theory
- Network and Multi User Information Theory
- Information Geometry and Divergence Measures
- Advanced Coding, Coded Modulation and Neural Compression
- Sequence Design, Data Compression and Sampling Theory
- Information Theoretic Cryptography and Complexity
- Quantum Information Theory, Quantum Coding and Thermodynamics
- DNA Storage, Genomics and Biological Information Theory
- AI Native Waveform Design and Integrated Sensing Communication
- Semantic and Goal Oriented Communications
- Deep Learning for Communications and Wireless Embodied Intelligence
- Optical, Wireless, IoT and TE QKD Systems
- Information Theoretic Machine Learning
- Learning, Inference and Bayesian Information Theory
- Information Theory for Generative AI and Diffusion Models
- Multimodal Information Theory and Foundation Model Alignment
- Representation Learning and Information Bottleneck
- Information Theoretic AI Safety, Robustness and Privacy
- Information Theory for Large Language Models (LLMs)
- Information Theory for Foundation Models and Scaling Laws
- Information Theory for RAG and Memory Systems
- Information Theory for Edge Deployed LLMs
- Federated Learning and Federated Foundation Models
- Information Theory for Graph Neural Networks
- Information Theory for Reinforcement Learning
- Information Theory for Neuromorphic and Spiking AI
- Information Theory for Synthetic Data and Data Generation
- Information Theory for Digital Twins and Cyber Physical Systems
- Information Theory for Autonomous and Intelligent Systems
- Information Theory for Time Series and Dynamical Systems
Paper Submission
Authors are invited to submit papers through the conference Submission System by October 10, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed).
Selected papers from ITEORY 2026, after further revisions, will be published in the special issue of the following journals.
Important Dates
| Submission Deadline | : | October 10, 2026 |
| Authors Notification | : | November 02, 2026 |
| Final Manuscript Due | : | November 06, 2026 |
Co - Located Event
***** The invited talk proposals can be submitted to iteory@comsap2026.org
