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Learning and Intelligent Optimization Conference

Learning and Intelligent Optimization Conference

Nice, France

Submission Deadline: Monday 23 Jan 2023

Conference Dates: Jun 04, 2023 - Jun 08, 2023

Research
Impact Score 0.30

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Ranking & Metrics Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.

Research Impact Score: 0.30
Contributing Best Scientists: 3
H5-index:
Papers published by Best Scientists 5
Research Ranking (Computer Science) 600
Research Ranking (Mathematics) 55

Conference Call for Papers

The central theme of this conference is ML to OR pipelines. When integrating multiple data science pipelines, significant challenges arise, especially when considering predictive and prescriptive analytics. Central challenges here include loss functions for training ML models that will be used downstream by optimization approaches and actively taking uncertainty into account in optimization models. This joins with classic LION themes, such as determining appropriate optimization methods through expensive algorithm configuration and parameter tuning , implementing intelligent learning schemes for learning from past algorithm behavior to improve performance in the future, hybridizing different algorithms (evolutionary, etc.) to achieve robust and effective performance, and so on.

Overview

Top Research Topics at Learning and Intelligent Optimization?

  • Mathematical optimization (51.07%)
  • Algorithm (21.67%)
  • Artificial intelligence (20.60%)

Learning and Intelligent Optimization primarily tackles Mathematical optimization, Algorithm, Artificial intelligence, Set (abstract data type) and Optimization problem. Mathematical optimization study tackled is connected to the field of Benchmark (computing). Learning and Intelligent Optimization explores research in Algorithm and the adjacent study of Solver.

While it focused on Artificial intelligence, it was also able to explore topics like Machine learning, Data mining, Heuristics and Pattern recognition. The work tackled in the conference goes beyond the discipline of Set (abstract data type) as it also encompasses Selection (genetic algorithm). In particular, the Optimization problem works presented emphasize discussions on Test functions for optimization.

Local search (optimization) research presented is mostly focused on the subject of Guided Local Search.

What are the most cited papers published at the conference?

  • Sequential model-based optimization for general algorithm configuration (1465 citations)
  • Continuous upper confidence trees (83 citations)
  • Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection (76 citations)

Research areas of the most cited articles at Learning and Intelligent Optimization:

The most cited publications mostly deal with topics like Mathematical optimization, Optimization problem, Artificial intelligence, Machine learning and Evolutionary algorithm. The most cited papers hold forums on Mathematical optimization that merge themes from other disciplines such as Range (mathematics) and Set (abstract data type). The published papers facilitate discussions in Heuristic and Selection (genetic algorithm) as part of the larger field of Artificial intelligence, however, they also tackle fields such as Occupancy rate.

What topics the last edition of the conference is best known for?

  • Artificial intelligence
  • Statistics
  • Machine learning

The previous edition focused in particular on these issues:

The conference focuses on Mathematical optimization, Artificial intelligence, Multi-objective optimization, Set (abstract data type) and Selection (genetic algorithm). The conference focuses on Mathematical optimization research which is adjacent to topics in Algorithm. The study of Machine learning and how it intertwines with concepts under Solver and Function (engineering) were explored in the presented Artificial intelligence research.

It facilitates discussions on Multi-objective optimization that incorporate concepts from other fields like Function (mathematics), Simulated annealing and Unary operation. It facilitates discussions in Pareto optimal as part of the larger field of Set (abstract data type), however, it also tackles fields such as Benchmarking. The conference focuses on Selection (genetic algorithm) but the discussions also offer insight into other areas such as Computer experiment, Bayesian optimization, Parallel optimization and Benchmark (computing).

The most cited articles from the last conference are:

  • Fast Computation of the Multi-Points Expected Improvement with Applications in Batch Selection (76 citations)
  • R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection (69 citations)
  • Identifying Key Algorithm Parameters and Instance Features Using Forward Selection (49 citations)

Papers citation over time

A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Research.com

The top authors publishing at Learning and Intelligent Optimization (based on the number of publications) are:

  • Laetitia Jourdan (6 papers) published 2 papers at the last edition, 1 less than at the previous edition,
  • Holger H. Hoos (6 papers) published 3 papers at the last edition, 1 more than at the previous edition,
  • Clarisse Dhaenens (5 papers) published 2 papers at the last edition, 1 less than at the previous edition,
  • Sébastien Verel (5 papers) published 1 paper at the last edition, 3 less than at the previous edition,
  • Kevin Leyton-Brown (4 papers) published 1 paper at the last edition, 1 less than at the previous edition.

The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.

Research.com

Only papers with recognized affiliations are considered

The top affiliations publishing at Learning and Intelligent Optimization (based on the number of publications) are:

  • French Institute for Research in Computer Science and Automation (9 papers) published 1 paper at the last edition, 3 less than at the previous edition,
  • University of Granada (8 papers) published 4 papers at the last edition, 2 more than at the previous edition,
  • Université libre de Bruxelles (7 papers) published 5 papers at the last edition, 4 more than at the previous edition,
  • University of British Columbia (6 papers) published 3 papers at the last edition, 1 more than at the previous edition,
  • University of Nottingham (5 papers) published 1 paper at the last edition, 2 less than at the previous edition.

The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.

Research.com

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

Research.com

During the most recent 2013 edition, 2.04% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 45.83% were posted by at least one author from the top 10 institutions publishing at the conference. Another 6.25% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.67% of all publications and 31.25% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.

Research.com

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

Research.com

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

Research.com

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Research.com

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Previous Editions

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