Topic Areas

NEURAL NETWORK MODELS

Feedforward neural networks

Recurrent neural networks

Self-organizing maps

Radial basis function networks

Attractor neural networks and associative memory

Modular networks

Fuzzy neural networks

Spiking neural networks

Reservoir networks (echo-state networks, liquid-state machines, etc.)

Large-scale neural networks

Other topics in artificial neural networks

FUZZY SETS AND SYSTEMS

Mathematical and theoretical foundations of fuzzy sets, fuzzy measures, and fuzzy integrals

Interpretable and Interactive approaches to uncertainty in AI

Fuzzy data analysis, fuzzy clustering, classification and pattern recognition

Type-2 fuzzy sets, computing with words, and granular computing

Fuzzy systems design and optimization

Applications of fuzzy sets and systems, fuzzy measures and integrals

Fuzzy and uncertain information processing, information extraction, and fusion

Theory and applications of imprecise probabilities and possibilities

Neuro- and evolutionary-fuzzy systems

EVOLUTIONARY COMPUTATION

Ant colony optimization

Particle swarm optimization

Genetic algorithms

Differential evolution

Parallel and distributed algorithms

Meta-modeling and surrogate models

Evolutionary simulation-based optimization

Discrete and combinatorial optimization

Multi-objective evolutionary algorithms

Evolutionary computation theory

Evolutionary programming

Evolved neural networks

Evolutionary fuzzy systems

Evolved neuro-fuzzy systems

MACHINE LEARNING

Unsupervised learning and clustering, (including PCA, and ICA)

Reinforcement learning

Probabilistic and information-theoretic methods

Support vector machines and kernel methods

EM algorithms

Mixture models, ensemble learning, and other meta-learning or committee algorithms

Bayesian, belief, causal, and semantic networks

Statistical and pattern recognition algorithms

Visualization of data

Feature selection, extraction, and aggregation

Hybrid learning methods

Deep learning