The 9th Annual Conference on machine Learning, Optimization and Data science (LOD) is an international conference on machine learning, computational optimization, big data and artificial intelligence. The conference includes invited talks, tutorials, special sessions, industrial tracks, demonstrations, and oral and poster presentations of refereed papers.
The LOD has established itself as a premier interdisciplinary conference in machine learning, computational optimization, data science and AI. It provides an international forum for the presentation of original interdisciplinary research results, and the exchange and dissemination of innovative and practical development experiences.
We invite submissions of papers, abstracts, posters, talks and demos on all topics related to Machine learning, Optimization and Data Science including real-world applications for the Conference Post-Proceedings – Springer-Nature Lecture Notes in Computer Science (LNCS).
The LOD Conference Manifesto
“The problem of understanding intelligence is said to be the greatest problem in science today and “the” problem for this century — as deciphering the genetic code was for the second half of the last one.
Arguably, the problem of learning represents a gateway to understanding intelligence in brains and machines, to discovering how the human brain works, and to making intelligent machines that learn from experience and improve their competences as children do.
In engineering, learning techniques would make it possible to develop software that can be quickly customized to deal with the increasing amount of information and the flood of data around us.”
“The Mathematics of Learning: Dealing with Data“
Tomaso Poggio (MOD 2015 & LOD 2020 Keynote Speaker)
&
Steve Smale
“Artificial Intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the Asilomar AI Principles, will offer amazing opportunities to help and empower people in the decades and centuries ahead.”
The Asilomar AI Principles have been adopted by the LOD Conference since their initial formulation (3-5 January 2017). Since then they have been an integral part of the Manifesto of the LOD Conferences (LOD 2017).
Keynote Speakers
Tutorial Speakers
General Chairs
Program Chairs
Special Sessions Chairs
Tutorial Sessions Chair
Industrial Session Chair
Publicity Chairs
Steering Committee
Platinum Sponsors
Gold Sponsors
Silver Sponsors
Bronze Sponsors
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Past Editions
Many international well-known experts in Machine Learning, Optimization and Big Data have joined LOD. Let’s review the history of LOD.
- LOD 2022
The Eighth International Conference on Machine Learning, Optimization and Big Data
Certosa di Pontignano, Siena – Tuscany, Italy.
Nature Springer – LNCS volumes 13810 and 13811. - LOD 2021
The Seventh International Conference on Machine Learning, Optimization and Big Data
Grasmere – Lake District – England, UK.
Nature Springer – LNCS volumes 13163 and 13164. - LOD 2020
The Sixth International Conference on Machine Learning, Optimization and Big Data
Castelnuovo Berardenga – Tuscany – Italy.
Nature Springer – LNCS volumes 12565 and 12566. - LOD 2019
The Fifth International Conference on Machine Learning, Optimization and Big Data
Castelnuovo Berardenga – Tuscany – Italy.
Nature Springer – LNCS volume 11943. - LOD 2018
The Fourth International Conference on Machine Learning, Optimization and Big Data
Volterra – Tuscany – Italy.
Nature Springer – LNCS volume 11331. - MOD 2017
The Third International Conference on Machine Learning, Optimization and Big Data
Volterra – Tuscany – Italy.
Springer – LNCS volume 10710. - MOD 2016
The Second International Workshop on Machine learning, Optimization and big Data
Volterra – Tuscany – Italy.
Springer – LNCS volume 10122. - MOD 2015
International Workshop on Machine learning, Optimization and big Data
Taormina – Sicily – Italy.
Springer – LNCS volume 9432.
