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DTSTART;VALUE=DATE:20200727
DTEND;VALUE=DATE:20200801
DTSTAMP:20260415T163805
CREATED:20200211T141324Z
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SUMMARY:MESS 2020 ~ Learning & Optimization from Big Data ~ Catania\, 27-31 July 2020
DESCRIPTION:MESS 2020 – Metaheuristics Summer School\n– Learning & Optimization from Big Data –\n27-31 July 2020\, Catania\, Italy \nMESS 2020 Webpage\nmess.school@ANTs-lab.it\nMESS on Facebook\n———————————————————————– \n*** ONCE MONTH LEFT!!! *** \n** APPLICATION DEADLINE: 5th March 2020 **\nhttps://www.ants-lab.it/mess2020/application/ \nMESS 2020 is aimed at qualified and strongly motivated MSc and PhD\nstudents; post-docs; young researchers\, and both academic and\nindustrial professionals to provide an overview on the several\nmetaheuristics techniques\, and an in-depth analysis of the\nstate-of-the-art. The main theme of the 2020 edition is ?Learning and\nOptimization from Big Data?\, therefore MESS 2020 wants to focus on (i)\nLearning for Metaheuristics; (ii) Optimization in Machine Learning;\nand (iii) how Optimization and Learning affect the Metaheuristics\nmaking them relevant in handling Big Data. \nAll participants will have plenty of opportunities for debate and work\nwith leaders in the field\, benefiting from direct interaction and\ndiscussions in a stimulating environment. They will also have the\npossibility to present their recently results and/or their working in\nprogress through oral or poster presentations\, and interact with their\nscientific peers\, in a friendly and constructive environment. \nParticipants will be delivered a certificate of attendance indicating\nthe number of hours of lectures (36-40 hours of lectures). In\naccording to the academic system all PhD and master students attending\nto the summer school will may get 8 ECTS points. \n** LIST OF LECTURERS \n+ Angelo Cangelosi\, University of Manchester & Alan Turing Institute\, UK\n+ Swagatam Das\, Indian Statistical Institute\, Kolkata\n+ Luca Maria Gambardella\, IDSIA Istituto Dalle Molle for Artificial\nIntelligence\, Switzerland\n+ Salvatore Greco\, University of Catania\, Italy & University of Portsmouth\, UK\n+ Emma Hart\, Edinburgh Napier University\, UK\n+ Mauricio Resende\, AMAZON\, USA\n+ Roman Slowinski\, Pozna? University of Technology\, Poland\n+ El-Ghazali Talbi\, University of Lille 1\, France\n+ Daniele Vigo\, University of Bologna\, Italy \nMore Lecturers will be announced soon. \n** SCHOOL DIRECTORS \n+ Pascal Bouvry\, University of Luxembourg\, Luxembourg\n+ Salvatore Greco\, University of Catania\, Italy\n+ Ender Ozcan\, University of Nottingham\, UK\n+ Mario Pavone\, University of Catania\, Italy\n+ El-Ghazali Talbi\, University of Lille 1\, France\n+ Daniele Vigo\, University of Bologna\, Italy \n** METAHEURISTICS COMPETITION \nAll participants to the school will be involved in the ?Metaheuristics\nCompetition?\, where each of them will must develop a metaheuristic\nsolution on the given problem. The top three of the competition\nranking will receive the MESS 2020 prize. Students whose algorithm\nwill rank in the first five top of the competition ranking\, will be\ninvited to submit a report/manuscript of their work to be published in\nthe special MESS 2020 Volume of the AIRO Springer Series. \n** METAHEURISTICS COMPETITION CHAIRS \n+ Raffaele Cerulli\, University of Salerno\, Italy\n+ Andrea Schaerf\, University of Udine\, Italy \n** SHORT TALK & POSTER PRESENTATION \nAll participants may submit an abstract of their recent results\, or\nworks in progress\, for presentation and having the opportunities for\ndebate and interact with leaders in the field. Mini-Workshop\nOrganizers and Scientific Committee will review the abstracts and will\nrecommend for the format of the presentation (oral or poster). All\nabstracts will be published on the electronic hands-out book of the\nsummer school. \nThe Abstracts must be submitted by *March 5\, 2020*. \n** WORKSHOP CHAIRS \n+ Vincenzo Cutello\, University of Catania\, Italy\n+ Paola Festa\, University of Naples ?Federico II?\, Italy\n+ Isaac Triguero\, University of Nottingham\, UK \n*See Previous Edition – MESS 2018*\nhttps://www.ants-lab.it/mess2018/ \n** MORE INFORMATION: \nhttps://www.ants-lab.it/mess2020/   —   mess.school@ANTs-lab.it\nFacebook Group: https://www.facebook.com/groups/MetaheuristicsSchool/\nTwitter: https://twitter.com/MESS_school
URL:https://www.euro-online.org/websites/eume/event/mess-2020-learning-optimization-from-big-data-catania-27-31-july-2020/
LOCATION:Catania\, Sicily\, Italy
CATEGORIES:Schools
ATTACH;FMTTYPE=image/jpeg:https://www.euro-online.org/websites/eume/wp-content/uploads/sites/6/2020/02/cropped-img-title-1.jpg
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20210615
DTEND;VALUE=DATE:20210619
DTSTAMP:20260415T163805
CREATED:20210128T105224Z
LAST-MODIFIED:20210128T105224Z
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SUMMARY:MESS 2020+1 ~ Learning & Optimization from Big Data ~ 15-18 June 2021
DESCRIPTION:———————————————————————– \nMESS 2020+1 – Metaheuristics Summer School\n– Learning & Optimization from Big Data –\n15-18 June 2021\, Catania\, Italy (virtual and onsite mode) \nhttps://www.ANTs-lab.it/mess2020/ \nmess.school@ANTs-lab.it \nhttps://www.facebook.com/groups/MetaheuristicsSchool/ ———————————————————————– \n** APPLICATION DEADLINE: 5th March 2021 **||\nhttps://www.ants-lab.it/mess2020/application/ \nMESS 2020+1 is aimed at qualified and strongly motivated MSc and PhD students; post-docs; young researchers\, and both academic and industrial professionals to provide an overview on the several metaheuristics techniques\, and an in-depth analysis of the state-of-the-art. The main theme of this edition is “Learning and Optimization from Big Data”\, therefore MESS 2020+1 wants to focus on (i) Learning for Metaheuristics; (ii) Optimization in Machine Learning; and (iii) how Optimization and Learning affect the Metaheuristics making them relevant in handling Big Data. \nParticipants will be delivered a certificate of attendance indicating the number of hours of lectures (36-40 hours of lectures). In according to the academic system all PhD and master students attending to the summer school will may get 8 ECTS points. \n** LIST OF LECTURERS & LECTURES TITLES \n+ Paolo Arena\, Unviersity of Catania\, Italy\nLecture#1: TBA\nLecture#2: TBA \n+ Angelo Cangelosi\, University of Manchester & Alan Turing Institute\, UK\nLecture#1: Cognitive and Developmental Robotics\, part 1\nLecture#2: Cognitive and Developmental Robotics\, part 2 \n+ Swagatam Das\, Indian Statistical Institute\, Kolkata\nLecture#1: Deep Generative Adversarial Networks and Their Application to Class-imbalanced Learning\nLecture#2: Non-convex Constrained Optimization – Some Advanced Approaches \n+ Luca Maria Gambardella\, IDSIA Istituto Dalle Molle for Artificial Intelligence\, Switzerland\nLecture#1: TBA\nLecture#2: TBA \n+ Salvatore Greco\, University of Catania\, Italy & University of Portsmouth\, UK\nLecture#1: Preference Learning in Multicriteria Decision Support\nLecture#2: Evolutionary Multiobjective Optimization Guided by Preference Learning \n+ Giuseppe F. Italiano\, Luiss University\, Italy\nLecture#1: TBA\nLecture#2: TBA \n+ Rafael Martì\, University of Valencia\, Spain\nLecture#1: Optimization in Graph Drawing\nLecture#2: Models and Heuristics in Discrete Diversity Maximization \n+ Gabriela Ochoa\, University of Stirling\, UK\nLecture#1: Fitness Landscape Analysis\nLecture#2: Complex Networks in Search and Optimisation \n+ Mauricio Resende\, AMAZON\, USA\nLecture#1: GRASP with Path-Relinking for Real-World Optimization Problems\nLecture#2: Biased Random-Key Genetic Algorithms with Applications \n+ El-Ghazali Talbi\, University of Lille 1\, France\nLecture#1: Machine learning for metaheuristics\nLecture#2: Automated design of deep neural networks \n+ Daniele Vigo\, University of Bologna\, Italy\nLecture#1: Fast and scalable heuristics for vehicle routing problems\nLecture#2: Integrating machine learning into vehicle routing heuristics \n** METAHEURISTICS COMPETITION \nAll participants to the school will be involved in the “Metaheuristics Competition”\, where each of them will must develop a metaheuristic solution on the given problem. The top three of the competition ranking will receive the MESS 2020+1 prize. Students whose algorithm will rank in the top ten of the competition ranking will be invited to submit a manuscript of their work to be published in the special volume MESS 2020+1 of the AIRO Springer Series. \n** SHORT TALK & POSTER PRESENTATION \nAll participants may submit an abstract of their recent results\, or works in progress\, for presentation and having the opportunities for debate and interact with leaders in the field. Mini-Workshop Organizers and Scientific Committee will review the abstracts and will recommend for the format of the presentation (oral or poster). All abstracts will be published on the electronic hands-out book of the summer school. \nThe Abstracts must be submitted by *March 5\, 2020*. \n*See Previous Edition – MESS 2018*\nhttps://www.ants-lab.it/mess2018/ \n** MORE INFORMATION: \nhttps://www.ANTs-lab.it/mess2020/ — mess.school@ANTs-lab.it Facebook Group: https://www.facebook.com/groups/MetaheuristicsSchool/ Twitter: https://twitter.com/MESS_school
URL:https://www.euro-online.org/websites/eume/event/mess-20201-learning-optimization-from-big-data-15-18-june-2021/
LOCATION:Catania\, Sicily\, Italy
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DTSTART;TZID=UTC:20260608T080000
DTEND;TZID=UTC:20260611T170000
DTSTAMP:20260415T163805
CREATED:20260209T094219Z
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SUMMARY:MIC 2026 - 16th Metaheuristics International Conference
DESCRIPTION:MIC 2026 – 16th Metaheuristics International Conference\n\n8 – 11 June\, 2026\nIschia Island (Napoli)\, Italy \nwww.mic2026.unina.it \n*********************\nSubmission deadline: February 27\, 2026\nNumber of days to deadline: 21\n********************* \nAims\, Themes & Scope: As per tradition\, looking at the previous editions of the MIC conferences\, this conference focuses on the progress of the area of Metaheuristics and their applications and provides an opportunity to the international research community to discuss recent research results\, to develop new ideas and collaborations\, and to meet old friends and make new ones in relaxed atmosphere. MIC 2026 strives to propose a high-quality program that will be completed by a number of invited talks\, tutorials\, workshops and special sessions. \nSolicited contributions can cover a variety of topics including but not limited to:\n– Metaheuristic techniques such as tabu search\, simulated annealing\, iterated local search\, variable neighborhood search\, memory-based optimization\, dynamic local search\, evolutionary algorithms\, memetic algorithms\, ant colony optimization\, particle swarm optimization\, scatter search\, path relinking\, etc.\n– Techniques that enhance the usability and increase the potential of metaheuristic algorithms such as reactive search mechanisms for self-tuning\, offline metaheuristic algorithm configuration techniques\, algorithm portfolios\, parallelization of metaheuristic algorithms\, etc.\n– Empirical and theoretical research in metaheuristics including large-scale experimental analyses\, algorithm comparisons\, new experimental methodologies\, engineering methodologies for metaheuristic algorithms\, search space analysis\, theoretical insights into properties of metaheuristic algorithms\, etc.\n– High-impact applications of metaheuristics in fields such as bioinformatics\, electrical and mechanical engineering\, telecommunications\, sustainability\, business\, scheduling and timetabling. Particularly welcome are innovative applications\nof metaheuristic algorithms that have a potential of pushing research frontiers.\n– Contributions on the combination of metaheuristic techniques with those from other areas\, such as integer programming\, constraint programming\, machine learning\, etc.\n– Contributions on the use of metaheuristic techniques in machine learning and deep learning for finetuning and neural architecture search\, etc.\n– Challenging applications areas such as continuous\, mixed discrete-continuous\, multi-objective\, stochastic\, or dynamic problems. \nMIC 2026 accepts submissions in three different formats:\n1. Regular paper: novel and original research contributions of a maximum of 15 pages (LNCS format)\n2. Short paper: extended abstract of novel research works of 6 pages (LNCS format)\n3. Oral presentation: one page abstract describing the content of an high-quality manuscript that has recently\, within the last year\, been submitted or accepted for journal publication. \nAll submitted papers will undergo a review process. All papers must be prepared using Lecture Notes in Computer Science (LNCS) template\, and must be submitted in PDF using the easychair system (https://easychair.org/conferences?conf=mic2026). \nAccepted papers in categories 1 and 2 will be published as post-proceedings in Lecture Notes in Computer Science series by Springer. \nIn addition\, a post-conference special issue in Journal of Heuristics will be considered for the significantly extended and revised versions of selected accepted papers from categories 1 and 2. \nIMPORTANT DATES:\nAll deadlines are Anywhere on Earth (AoE = UTC-12h).\n– December 1\, 2025\, submission open/registration open\n– February 27\, 2026\, submission deadline\n– March 27\, 2026\, notification of acceptance\n– April 10\, 2026\, early registration deadline\n– June 8-11\, 2026\, conference at Ischia\, Italy \nCONTACT INFORMATION:\nPaola Festa (E-mail: infomic2026@unina.it\, paola.festa@unina.it)\nDept. of Mathematics and Applications “R. Caccioppoli”\, University of Napoli “Federico II”
URL:https://www.euro-online.org/websites/eume/event/mic-2026-16th-metaheuristics-international-conference/
LOCATION:ischia\, Ischia island (Napoli)\, Italy
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