Conference Information
MLANN 2026: Asia Conference on Machine Learning, Algorithms and Neural Networks
https://www.mlann.net/
Submission Date:
2026-02-20
Notification Date:
2026-03-20
Conference Date:
2026-05-22
Location:
Shanghai, China
Years:
4
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Call For Papers
Contributed papers are solicited describing original works in Machine Learning, Algorithms and Neural Networks. Topics and technical areas of interest include but are not limited to the following:

Machine Learning

Deep and Reinforcement Learning
Machine Learning for Network Slicing Optimization
Machine Learning for 5G system
Machine Learning for User Behavior Prediction
New Innovative Machine Learning Methods
Optimization of Machine Learning Methods
Performance Analysis of Machine Learning Algorithms
Experimental evaluations of machine learning
Machine learning for multimedia
Machine learning for Internet of Things
Machine learning for security and protection
Distributed and decentralized machine learning algorithms
Intelligent cloud-support communications
Intelligent ressource allocation
Intelligent energy-aware/green communications
Intelligent software defined networks
Intelligent cooperative networks
Intelligent positioning and navigation systems
Intelligent wireless communications
Intelligent wireless sensor networks
Intelligent underwater sensor networks

Algorithms	

Analysis of algorithms
Ant colony algorithm
Approximation algorithm
Combinatorial search
Competitive analysis
Computability theory
Computational complexity theory
Embarrassingly parallel problem
Emergent algorithm
Evolutionary algorithm
Genetic algorithm
Graph exploration algorithm
Las Vegas algorithm
Monte Carlo algorithm
Polynomial time approximation scheme
Quantum algorithm
Randomized algorithm
Sorting algorithm
Search algorithm
Super-recursive algorithm
Tree search algorithm
	
Neural Networks

Computational Science and Engineering
Deep learning
Signal processing
Information extraction
Natural language reasoning
Pattern recognition
Image processing and Computer vision
Machine translation
Active learning
Domain adaptation
Sequence to sequence learning
Professional system
Study on one's own
Robot control
Combinatorial optimization
Knowledge engineering
Artificial intelligence
Programming in logic
Human-computer interaction
Optimal combination
Logic programming
Last updated by Dou Sun in 2026-01-07
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