Call for Papers

The organizers solicit previously unpublished papers offering novel research contributions in any aspect of machine learning, metaheuristics and their applications.

The major areas of interest include, but are not limited to, the following topics:

Metaheuristics Algorithms

  • Animal Migration Optimization
  • Ant Colony Optimization
  • Ant Lion Optimization Algorithm
  • Artificial Algae Algorithm
  • Artificial Bee Colony Algorithm
  • Artificial Chemical Process Algorithm
  • Artificial Ecosystem Algorithm
  • Artificial Fish Swarm Optimization
  • Artificial Immune Systems
  • Bacterial Evolutionary Algorithm
  • Bat Algorithm
  • Bird Mating Optimizer
  • Bull Optimisation Algorithm
  • Bumble Bees Mating Optimization
  • Cellular Automata
  • Central Force Optimization
  • Chaos Optimization Algorithm
  • Chemical Reaction Algorithm
  • Chicken Swarm Optimization
  • Collective Animal Behavior
  • Construct, Merge, Solve & Adapt
  • Coral Reefs Optimization
  • Cuckoo Search
  • Cultural Algorithms
  • Cuttlefish Algorithm
  • Differential Evolution
  • Dragonfly Algorithm
  • Earthworm Optimization
  • Elephant Herd Algorithm
  • Emperor Penguins Colony
  • Evolutionary Computation and Metaheuristics
  • Firefly Algorithm
  • Forest Optimization Algorithm
  • Fuzzy-metaheuristic Methods
  • Genetic Programming
  • Grasshopper Optimization Algorithm
  • Gravitational Search Algorithm
  • Greedy Randomized Adaptive Search
  • Grey Wolf Optimizer
  • Group Search Optimizer
  • Guided Local Search & Fast Local Search
  • Harmony Search
  • Honey-Bees Mating Optimization
  • Hunting Search Algorithm
  • Krill Herd Algorithm
  • Intelligent Water Drops Algorithm
  • Iterated Local Search
  • Locust Search Algorithm
  • Memetic Algorithms
  • Meta-Heuristic Algorithms for Deep Learning
  • Mine Blast Algorithm
  • Monarch Butterfly Optimization
  • Moth-Flame Optimization Algorithm
  • Multi-objective Optimisation
  • Multiple Operator Metaheuristics
  • Neighborhood Search Metaheuristics
  • Parliamentary Optimization Algorithm
  • Particle Swarm Optimization
  • Photosynthetic and Enzyme Algorithm
  • Physarum Polycephalum Algorithm
  • Population Based Metaheuristics
  • Rainfall Optimization Algorithm
  • River Formation Dynamics
  • Roach Infestation Optimization
  • Salp Swarm Algorithm
  • Scatter Search
  • Seed-Based Plant Propagation Algorithm
  • Sheep Flocks Heredity Model Algorithm
  • Shuffled Frog Leaping Algorithm
  • Simulated Annealing
  • Social Cognitive Optimization
  • Social Spider Optimization
  • Sperm Swarm Optimization Algorithm
  • Spiral Optimization Algorithm
  • Stellar-Mass Black Hole Optimization
  • Stochastic Search
  • Strawberry Algorithm
  • Tabu Search
  • Teaching-Learning-Based Optimization
  • Team Game Algorithm
  • The States of Matter Search
  • Tree Physiology Optimization
  • Variable Neighbourhood Search
  • Water Wave Optimization
  • Whale Optimization Algorithm
  • Wind-Driven Optimization

Machine Learning Techniques

  • Adversarial Learning
  • Analogical Learning Methods
  • Bayesian Models and Methods
  • Bayesian Networks
  • Biologically Inspired Machine Learning
  • Case-Based Reasoning and Associative Memory
  • Classification and Clustering
  • Cognitive Modeling
  • Collaborative Filtering
  • Computational Learning Theory
  • Conceptional Learning and Clustering
  • Connectionist Networks
  • Convolutional Neural Networks
  • Cooperative Machine Learning
  • Deep Learning
  • Distributed Machine Learning
  • Embedded Machine Learning
  • Ensemble Methods
  • Evolutionary Computation and Deep Neural Networks
  • Explanation-Based Learning
  • Feature Learning
  • Formal Modeling for Machine Learning Techniques
  • Fuzzy Logic and Machine Learning
  • Genetic Algorithms and Machine Learning
  • Graphical Models
  • Hybrid Learning Algorithms
  • Indefinite Proximity Learning
  • Inductive Learning
  • Kernel Machines K-Nearest Neighbor Classifier
  • Knowledge Representation in Machine Learning
  • Large-Scale Machine Learning
  • Learning Decision and Regression Trees
  • Learning through Fuzzy Logic
  • Loopy Belief Propagation
  • Multi-Agent Learning
  • Multi-Strategy Learning
  • Neural Network Learning
  • Online and Incremental Learning
  • Organisational Learning and Evolutional Learning
  • Recurrent Network Architectures
  • Reinforcement Learning
  • Relevance Vector Machine
  • Rough Sets Theory and Machine Learning
  • Scalability of Learning Algorithms
  • Secure Machine Learning Algorithms
  • Statistical and Evolutionary Learning
  • Stochastic Gradient Descent
  • Support Vector Machine
  • Time Series and Sequential Pattern Mining
  • Transfer Learning
  • Self-Organizing Maps and Vector Quantization

Applications of Machine Learning and Meta-heuristic Algorithms

  • Affective Computing
  • Autonomic Control Systems
  • Automatic Driving
  • Behavioural Analytics/Graph Analytics
  • Biometric Applications
  • Blockchain and Deep Learning
  • Brain-Computer Interfaces
  • Cognitive Imaging and Processing
  • Cognitive Radio Networks
  • Computer Vision & Image Processing
  • Context-Awareness and Intelligent Environment Applications
  • Cyber-Physical Systems
  • Cyber Defense
  • Data Analysis and Intelligent Optimization
  • Digital Forensics
  • Digital Twin/AI Modeling
  • Emotion Recognition
  • Experience Economy/Financial Engineering and Time Series Forecasting
  • Game Playing and Problem Solving
  • Hyper Personalisation
  • Intelligent Cloud and Intelligent Edge
  • Intelligent Human-Computer Interaction
  • Intrusion Detection Systems
  • Intelligent Transport Systems and Smart Mobility
  • Intelligent Virtual Environments
  • Internet of Things and Sensor Networks
  • Multi-sensor Intelligent Information Fusion
  • Neuroscience and Behavior Analysis in Robotics
  • Neuromorphic Computing
  • Online Social Networks
  • Pattern Recognition
  • Peer-to-Peer Networks
  • Recommender Systems
  • Smart Grid
  • Smart Surveillance Systems
  • Smart Healthcare and Disease Analytics
  • Smart Living and Smart Cities
  • Speech and Natural Language Processing
  • Trust Management

All papers that conform to submission guidelines will be peer reviewed and evaluated based on originality, technical and/or research content/depth, correctness, relevance to conference, contributions, and readability. Acceptance of papers will be communicated to authors by email.

All accepted papers will be published in the proceedings. To be published in the Conference Proceedings, an author of an accepted paper is required to register for the conference at the full rate.

All accepted papers MUST be presented at the conference by one of the authors, or, if none of the authors are able to attend, by a qualified surrogate.