Conference Information

OLA 2027: International Conference on Optimization and Learning

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Submission Date:
2026-12-18 Due in 56 days
Notification Date:
2027-01-23
Conference Date:
2027-05-05
Location:
Krakow, Poland
Viewed: 528   Tracked: 0   Attend: 0
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Conference Partner Index (CP-I)

43.6 / 100
Ranked #3,535 of 5,759 conferences · Top 62%
Limited evidence: this conference is not listed in CCF / ICORE / QUALIS and has no acceptance-rate data on file, so most of the score falls back to the neutral baseline.
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%) No data - scored at the neutral baseline of 50 —
Community attention (10%)
8
Public record completeness (15%)
35

Inputs used: Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 25% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.2 · Computed 2026-10-23

Call For Papers

OLA 2027 (International Conference on Optimization and Learning) is an academic conference held in Krakow, Poland on 2027-05-05. The paper submission deadline is 2026-12-18. Acceptance notifications are sent on 2027-01-23.

The International Conference in Optimization and Learning (OLA2027) focuses on the future challenges of optimization and learning methods and their applications. OLA2027 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. OLA2027 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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