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CTML--EI 2026 : 2026 International Conference on Computational Theory and Machine Learning (CTML 2026)

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Link: https://www.ctml.org/
 
When Nov 27, 2026 - Nov 29, 2026
Where Rio de Janeiro, Brazil
Submission Deadline Jun 30, 2026
Categories    cloud computing   deep learning   human-computer interaction   machine learning
 

Call For Papers

CTML 2026---Ei Compendex and Scopus

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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