International Conference on Learning and Optimization Algorithms: Theory and Applications

Track 1: Machine learning

• Deep learning Algorithms
• Density Estimation algorithms
• Model selection Algorithms
• Performance study of learning algorithms
• Feature selection Algorithms
• Sampling Algorithms
• Supervised  learning algorithms
• Unsupervised learning algorithms
• Semi-Supervised Learning algorithms
• Reinforcement learning algorithms
• Similarity algorithms
• Dimensionality Reduction Algorithms
• Association Rule Learning Algorithms
• Subgroup discovery
• Multiclass learning algorithms
• Boosting learning algorithms
• Regression Algorithms
• Instance-based Algorithms
• Regularization Algorithms
• Multi-instance learning
• Multilabel classification
• Multi-View Learning
• Text mining
• Data Preprocessing

Track 2: Optimization 

• Stochastic Optimization
• Nonlinear Optimization
• Combinatorial optimization
• Bi-level Optimization
• Multiobjective Optimization
• Optimal Control
• Linear Optimization
• Dynamic Programming
• Meataheuristics
• Local search metaheuristics
• Tuning of optimization algorithms
• Control of optimization algorithms
• Algorithm selection for software engineering
• Performance study of optimization algorithms
• Evolutionary and Bioinspired Algorithms

Track 3: Swarm Intelligence  

• Control in swarm  intelligence
• Configuration of swarm intelligence algorithms
• Topological study of swarm intelligence algorithms
• Collaborative strategies in  swarm  intelligence and multi-swarm
• Swarm robotics

Track 4: Forecasting 

• Integration of learning in forecasting
• Hybridization of forecasting models with machine learning
• Integration of optimization in the setting of the forecasting models
• Application of learning forecasting in Commodities – Electricity- Logistics-Finance

Track 5: Social Media Analytics  

• Community analysis
• Information Diffusion in Social Media
• Social Network analysis
• Recommendation Systems
• Information retrieval
• Web mining
• Image and video processing
• Sentiment analysis
• Natural Language Processing

Track 6: Big Data Analytics  

• Big Data novel theory, algorithm and application
• Volume, Velocity, Variety, Value and Veracity of Big Data
• MapReduce for Big Data processing
• Distributed file systems for Big Data
• Big Data visualization
• Big Data mining 
• Large data stream processing
• Performance characterization, evaluation and optimization
• Sensor network, social network and big data
• Big data applications

Track 7: Cloud Computing Algorithms  

• Data-driven algorithms and applications
• Grid and distributed algorithms
• Parallel and GPU Computing
• Large Scale Processing
• Cloud Data Analysis Algorithms
• Cloud resource management
• Security in cloud 
• Load balancing algorithms for cloud computing