Track 1
Machine Learning and AI for Data Analysis
- Deep Learning for Time Series Analysis
- Reinforcement Learning for Big Data Decision Making
- Federated Learning for Privacy-Preserving AI in Healthcare
- Explainable AI (XAI) for Data-Driven Decision Making
- Generative Adversarial Networks (GANs) for Data Augmentation in Healthcare
- Transfer Learning for Efficient Data Analysis
- Graph Neural Networks (GNNs) for Complex Data Analysis
- AutoML for Data Analysis Automation
Track 2
Neural Networks and Fuzzy Systems
- Deep Reinforcement Learning for Complex Decision Making
- Spiking Neural Networks (SNNs) for Energy-Efficient Computing
- Hybrid Neural-Fuzzy Systems for Uncertainty Handling
- Generative Adversarial Networks (GANs) for Data Synthesis and Augmentation
- Convolutional Neural Networks (CNNs) for Image and Video Analysis
- Recurrent Neural Networks (RNNs) for Sequential Data Analysis
- Self-Supervised Learning for Pre-Training Neural Networks
- Attention Mechanisms in Neural Networks
Track 3
Intelligent Agent Technologies
- Multi-Agent Systems for Collaborative Problem-Solving
- Agent-Based Modeling for Complex Systems
- Reinforcement Learning for Agent-Based Systems
- Explainable AI for Intelligent Agents
- Human-Agent Interaction
- Autonomous Agents for Robotics
- Agent-Based Learning from Human Demonstrations