CONFERENCES

CTML 2026
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2026 International Conference on Computational Theory and Machine Learning

posted by organizer: ||1 views||Release time:Mar 19, 2026

Conference DateNov 27-Nov 29, 2026PlaceRio de Janeiro, Brazil
Submission DeadlineJun 30, 2026E-mailctmlconf@163.com
Websitehttps://www.ctml.org/Telephone
DESCRIPTION
Full Name: 2026 International Conference on Computational Theory and Machine Learning (CTML 2026) Acronym: CTML 2026 Place: Rio de Janeiro, Brazil Date: November 27-29, 2026 Website: https://www.ctml.org/ Organizer: India International Congress on Computational Intelligence(IICCI) The International Conference on Computational Theory and Machine Learning (CTML 2026) will be held in Rio de Janeiro, Brazil, during November 27-29, 2026. This conference focuses on computational theory, machine learning foundations, algorithm design, and related interdisciplinary research. It provides a high-level academic platform for global researchers, scholars, and practitioners to share innovative findings, exchange ideas, and promote academic cooperation. CTML 2026 welcomes high-quality papers and presentations, aiming to advance theoretical progress and practical applications in computational theory and machine learning. ☛ CALL FOR PAPERS Authors are invited to submit full papers describing original research work in areas including, but not limited to: TRACK 1: Foundations of Computational Learning Statistical Learning Theory and Generalization Computational Complexity of Learning Online Learning and Regret Analysis Learning Dynamics and Convergence Scaling Laws and Emergent Behavior in Large Models PAC-Bayes Theory and Algorithmic Stability TRACK 2: Deep Learning Theory and Neural Architectures Expressivity and Capacity of Neural Networks Theoretical Analysis of Transformers and Foundation Models Neural Network Optimization Landscapes Overparameterization and Double Descent Implicit Regularization and Bias of Gradient Methods Mechanistic Interpretability and Model Internals Physics-Informed Neural Networks and Neural Operators TRACK 3: Optimization and Algorithms for Machine Learning Convex and Non-Convex Optimization Evolutionary Algorithms and Metaheuristics Combinatorial Optimization in Learning Surrogate-Assisted and Expensive Optimization Optimization for Resource-Constrained Settings Federated Learning and Distributed Optimization Multi-Objective Optimization in ML Systems TRACK 4: Graph Theory, Combinatorics, and Learning on Structures Graph Neural Networks Theory Spectral Graph Theory and Applications Algorithmic Graph Theory and Network Analysis Combinatorial Optimization with Learning Random Graphs and Probabilistic Methods Geometric Deep Learning Learning on Manifolds and Non-Euclidean Data TRACK 5: Trustworthy and Explainable AI Causal Inference and Discovery Explainability and Interpretability Robustness, Uncertainty, and Calibration Privacy and Fairness in Machine Learning Adversarial Machine Learning Distribution Shift and Domain Generalization Safety and Alignment of AI Systems TRACK 6: AI for Scientific Discovery and Emerging Frontiers AI for Scientific Discovery Quantum Machine Learning Symbolic Regression and Scientific Law Discovery AI-Accelerated Scientific Computing Multi-Modal Learning and Fusion Computational Biology and AI for Healthcare Climate Modeling and Environmental AI TRACK 7: Efficient and Scalable Machine Learning Systems Model Compression and Knowledge Distillation Quantization and Pruning Neural Architecture Search Edge AI and TinyML Green AI and Energy-Efficient Learning Large-Scale Training Systems ML Compilers and Hardware-Software Co-Design For details about topics, please visit at https://www.ctml.org/cfp.html ☛ PUBLICATION ✿ Conference Proceedings Submissions will be reviewed by the conference technical committees, and accepted papers will be published in Conference Proceedings and submitted to EI Compendex, Scopus, etc. for indexing. ☛ SUBMISSION 1. Full Paper (Publication and Presentation) 2. Abstract (Presentation Only) For full paper(.pdf), please upload to https://www.zmeeting.org/submission/ctml2026 For abstract, please send it to ctmlconf@163.com More details about submission, please visit at https://www.ctml.org/submission.html ☛ CONFERENCE SCHEDULE November 27, 2026 10:30-17:00 Onsite Sign-in November 28, 2026 09:00-17:00 Registration 09:00-09:10 Opening Ceremony 09:10-09:55 Keynote 1 09:55-10:30 Group Photo & Coffee Break 10:30-11:15 Keynote 2 11:15-12:00 Keynote 3 12:00-13:30 Conference Lunch 13:30-15:30 Parallel Sessions 15:30-15:45 Coffee Break 15:45-18:00 Parallel Sessions 18:30-21:00 Conference Dinner November 29, 2026 All day Parallel Sessions ☛ CONTACT Mary Zhan (Conference Secretary) E-mail: ctmlconf@163.com

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