International Conference on Applications of Artificial Intelligence and Soft Computing Techniques in Engineering and Technology (AASTE 2014)

Key Topics

• Machine Learning
  Statistical learning theory, General Machine Learning Theory, Hierarchical learning models, Unsupervised and Supervised Learning, Meta learning, Relational learning models, Simulated annealing, Stochastic optimization, Neural networks, Heuristic optimization techniques, Multi-criteria reinforcement learning, Reinforcement learning, Decision making, Multiple hypothesis testing, Graphical models, Markov chain Monte Carlo (MCMC) methods, Cross-Entropy method, Gaussian graphical models, Time series prediction, Ant colony optimization, Inductive learning and applications, Fuzzy logic and learning, General Graph-based Machine Learning Techniques, Grammatical inference, Graph clustering, Graph-based semi-supervised learning, Graph learning based on graph matching, Graph learning based on graph transformations and grammars, Motif search, Information-theoretical approaches to graphs, General issues in graph and tree mining, Network inference, Induction of document grammars, Computational Intelligence, General Structure-based approaches in information retrieval, Supervised and unsupervised classification of web data, information extraction, web authoring, Latent semantic analysis, and web content mining, Aspects of text technology, Intelligent linguistic, Computational Statistics, Computational vision
• Artificial Intelligence
  Machine Translation, Natural language processing, Computer Science, Machine Transliteration, Algorithm and Programming, Computer Intelligence, Fuzzy logic and soft computing, Software Engineering, Expert systems, Software tools for AI, Automated problem solving, Decision support systems, Knowledge representation, Knowledge discovery, Knowledge-intensive problem solving techniques, Knowledge acquisition, Intelligent information systems, Knowledge networks and management, Intelligent agents, Intelligent web-based business, Intelligent user interface, Intelligent networks Intelligent databases, Intelligent tutoring systems, AI and evolutionary algorithms, Distributed AI algorithms and techniques, Reasoning strategies, Neural networks and applications, Distributed AI systems and architectures, Languages and programming techniques for AI, Heuristic searching methods, Search and meta-heuristics, Constraint-based reasoning and constraint programming Intelligent information fusion, Integration of AI with other technologies, Swarm Optimization, Social intelligence (markets and computational societies), Evaluation of AI tools, Emerging technologies Applications, Social impact of AI
• Soft Computing
  Neuro Computing, Fuzzy Computing, Probabilistic Computing, Evolutionary Computing, Hybrid Methods, Immunological Computing, Chaos Theory, Rough Sets, Ant Colony, Particle Swarm, Morphic Computing, Wavelet

Who should Attend

Academics and industrial experts in the field of Engineering and Technology.