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The organizers solicit previously unpublished papers offering novel research contributions in any aspect of machine learning, metaheuristics and their applications.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