Conference Information
MLCCIM 2024: International Conference on Machine Learning, Cloud Computing and Intelligent Mining
Submission Date:
Notification Date:
Conference Date:
Shennongjia, China
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Call For Papers
You are welcomed to submit your papers through the MLCCIM 2024 conference on topics which include:

Machine Learning (Part 1)
Reinforcement Learning Theory
Multiagent Deep Reinforcement Learning Theory & Applications
Reinforcement Learning in Game (including: Applications of Reinforcement Learning Based on Video Games, Application of Reinforcement Learning in Strategic Adversarial Games, The Reinforcement Learning Algorithm with Game Theory, etc.)
Reinforcement Learning in UAV (including: Applications of Reinforcement Learning in UAV Flight Stability Control, Multi-UAV Cluster Flight Control, UAVs’ Confrontation, and Multi-UAV Clusters’ Confrontation, etc.)
Reinforcement Learning in Robotics (including: Applications of Reinforcement Learning in Robotics Optimal Control and Multiagent Robotics Control, etc.)

Machine Learning (Part 2)
Robotics Optimal Control and Multiagent Robotics Control
Reinforcement Learning in Traffic (including: Applications of Reinforcement Learning in Traffic Light Control, Vehicles Control, Urban Path Planning, Autonomous Driving
Machine Learning Methods
Learning and Adaptive Control
Learning/Adaptation for Recognition and Perception
Learning for Handwriting Recognition
Learning in Image Pre-processing and Segmentation
Learning for Process Automation
Learning Appropriate Behavior
Learning of Action Pattern
Learning Robotics

Cloud Computing
Cloud and Grid Computing for Big Data
Cloud Application Architecture
Cloud Computing and Semantic Web Technologies
Cloud Computing Architectures and Systems
Cloud Computing Models, Simulations, Designs and Examples
Cloud Computing Technologies, Services and Applications
Cloud Middleware Frameworks
Cloud Optimization and Automation
Cloud Quality and Performance
Cloud Resource Virtualization and Synthesis
Cloud Solution Design Patterns
Distributed and Peer-to-Peer Search
Infrastructure and Platforms for Intelligent Computing
Models and Tools for Intelligent Computing

Intelligent Mining
Data Mining Algorithms
Data Analysis Fundamentals
Real-time Mining, Data Streams
Mining and dynamic Data Mining
Visual Mining and Data Visualization
Graph Mining and Semi-structured Data
Spatio-temporal Data Mining
Uncertainty Modeling in Data Mining
Web Mining
Intelligence-based Mata Mining Methods
Last updated by Dou Sun in 2024-02-01
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