March 8, 2018


CEC_01 Co-evolutionary games
CEC_02 Differential Evolution with Ensembles, Adaptations and Topologies
CEC_03 Multi-concept Optimization
CEC_04 Evolutionary Bilevel Optimization
CEC_05 Evolutionary Computation for Dynamic Optimization Problems
CEC_06 Applying Stopping Criteria in Evolutionary Multi-Objective Optimization
CEC_07 Dynamic Multi-objective Optimization: Challenges, Applications and Future Directions
CEC_08 Evolutionary Many-Objective Optimization
CEC_09 Pareto Optimization for Subset Selection: Theory and Applications in Machine Learning
CEC_10 Evolutionary Large-Scale Global Optimization: An Introduction
CEC_11 Representation in Evolutionary Computation
CEC_12 Parallel and distributed evolutionary algorithms
CEC_13 Evolutionary Algorithms and Hyperheuristics
CEC_14 Parallelization of Evolutionary Algorithms: MapReduce and Spark
CEC_15 Gentle Introduction to the Time Complexity Analysis of Evolutionary Algorithms
CEC_16 Constraint-Handling in Nature-Inspired Optimization
CEC_17 Machine Learning on Evolutionary Computation
CEC_18 Evolutionary Algorithms, Swarm Dynamics, and Complex Networks: Recent Advances and Progress

IJCNN_01 Deep Learning for Sequences
IJCNN_02 Deep Recurrent Neural Networks: Training and Applications in the Modeling and Control of Nonlinear Systems, Signal Processing and Robotics. [CANCELLED]
IJCNN_03 Prediction, Interaction, and User Behaviour
IJCNN_04 Entropic Evaluation of Classification. A hands-on, get-dirty introduction
IJCNN_05 Machine Learning for Spark Streaming with StreamDM
IJCNN_06 Learning class imbalanced data streams
IJCNN_07 Adaptive Resonance Theory in Social Media Clustering with Applications
IJCNN_08 Artificial Intelligence in Business (Changed to: Reinforcement Learning: Principles, Algorithms and Applications)
IJCNN_09 Non-Iterative Learning Methods for Classification and Forecasting
IJCNN_10 Graph based and Topological Unsupervised Machine Learning
IJCNN_11 Methods and Resources for Texture Classification
IJCNN_12 Tutorial on dynamic classifier selection: recent advances and perspectives
IJCNN_13 Deep, Transfer and Emergent Reinforcement Learning Techniques for Intelligent Agents
IJCNN_14 Neurosymbolic Learning and Reasoning with Constraints
IJCNN_15 Quest for the neural input: electrophysiology, source localization and causality analysis

FUZZ_01 Type-2 Fuzzy Sets and Systems
FUZZ_02 Fuzzy Systems in Medicine and Healthcare
FUZZ_03 Support Fuzzy Machines: From Kernels on Fuzzy Sets to Machine Learning Applications
FUZZ_04 Fuzzy Sets, Computer Science and (Fuzzy) Algorithms
FUZZ_05 Fuzzy Logic and Machine Learning
FUZZ_06 Uncertainty Modeling in Learning from Big Data

HYB_01 Computational Intelligence for Data Science and Big Data
HYB_02 Empirical Approach: How to get Fast, Interpretable Deep Learning
HYB_03 Interactive Adaptive Learning