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15th International Conference on Information Theory (IT 2026) serves as a premier global forum for presenting and discussing advances in the theory, methodology, and applications of Information Theory. The conference aims to bring together leading researchers, academics, and industry professionals to explore modern developments in the field and to foster meaningful collaboration across disciplines.

• Shannon Theory, Finite Blocklength Analysis, And Fundamental Limits • Coding Theory: Polar Codes, LDPC, Fountain Codes, And Modern Code Design • Multi User And Network Information Theory • Information Theory For Machine Learning And Deep Learning • Information Theoretic Generalization, Representation Learning, And Optimization • Information Bottleneck Methods And Rate Distortion Theory For ML Systems • Distributed Learning, Federated Learning, And Communication Efficient ML • Information Theory For Neural Compression And Learned Source/Channel Coding • Semantic And Goal Oriented Communications

Numerical Analysis and Computational Mathematics,    Systems theory, Control and Automation