The International Conference in Optimization and Learning (OLA2026) focuses on the future challenges of optimization and learning methods and their applications.
OLA2026 will provide an opportunity to the international research community in optimization and learning to discuss recent research results and to develop new ideas and collaborations in a friendly and relaxed atmosphere. OLA2026 welcomes presentations that cover any aspects of optimization and/or learning research such as:
- Optimization : Bayesian optimization, multi-objective optimization, global optimization, discrete optimization, mixed optimization, hybrid optimization, parallel optimization, simulation-based optimization, optimization under uncertainty, ...
- Learning : supervised, non supervised, deep models, neuromorphic models, federated learning, parallel/distributed learning ...
- Learning for optimization: deep learning, LLM, reinforcement learning, tuning, algorithm selection, algorithm generation, ...
- Optimization for learning : neural architecture search, hyper parameter optimization, model selection,
- Applications : Industry 4.0, bio-medical, operations research, energy, ...
- New computing paradigms : quantum computing, neuromorphic computing, ...
The conference. Additionally, selected long papers will be published in a Springer volume of Communications in Computer and Information Science (CCIS) series (SCOPUS indexed) indexed by SCOPUS, DBLP, EI Compendex, INSPEC, JST, SCImago, zbMATH, ...
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