LOD 2021: The Seventh International Conference on Machine Learning, Optimization, and Data Science - An Interdisciplinary Conference: Machine Learning, Optimization, Big Data & Artificial Intelligence without Borders The Wordsworth Hotel & SPA, Lake District Grasmere, UK, October 4-8, 2021 |
Conference website | https://lod2021.icas.cc |
Submission link | https://easychair.org/conferences/?conf=lod2021 |
Abstract registration deadline | June 15, 2021 |
Submission deadline | June 15, 2021 |
Abstract/Poster/Demo Submission Deadline: | June 25, 2021 |
Late-Breaking Paper Submission Deadline | June 25, 2021 |
Early Registration | July 31, 2021 |
The LOD Conferences: Asilomar AI Principles for interpretable, explainable and trustworthy AI
An Interdisciplinary Conference: Machine Learning, Deep Learning, Optimization, Big Data & Artificial Intelligence without Borders
Since 2015, the LOD Conference brings academics, researchers and industrial researchers together in a unique interdisciplinary community to discuss and present the state of the art and the latest advances in the integration of machine learning, optimization and data science to provide and support the scientific and technological foundations for interpretable, explainable and trustworthy AI. Since 2017, LOD adopted the Asilomar AI Principles.
The 7th Annual Conference on machine Learning, Optimization and Data science (LOD) is a international conference on machine learning, computational optimization and big data that includes invited talks, tutorial talks, 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 and data science. It provides an international forum for presentation of original interdisciplinary research results, as well as exchange and dissemination of innovative and practical development experiences.
Call for Papers - Submission Guidelines
Please prepare your paper in English using the Springer Nature – Lecture Notes in Computer Science (LNCS) template, which is available here. Papers must be submitted in PDF.
Types of Submissions
When submitting a paper to LOD 2021, authors are required to select one of the following four types of papers:
- long paper: original novel and unpublished work (max. 15 pages in Springer LNCS format);
- short paper: an extended abstract of novel work (max. 5 pages);
- work for oral presentation only (no page restriction; any format). For example, work already published elsewhere, which is relevant and which may solicit fruitful discussion at the conference;
- abstract for poster presentation only (max 2 pages; any format). The poster format for the presentation is A0 (118.9 cm high and 84.1 cm wide, respectively 46.8 x 33.1 inch). For research work which is relevant and which may solicit fruitful discussion at the conference.
Each paper submitted will be rigorously evaluated. The evaluation will ensure high interest and expertise of reviewers. Following the tradition of LOD, we expect high-quality papers in terms of their scientific contribution, rigor, correctness, novelty, clarity, quality of presentation and reproducibility of experiments.Accepted papers must contain significant novel results. Results can be either theoretical or empirical. Results will be judged on the degree to which they have been objectively established and/or their potential for scientific and technological impact.
Obviously, it is possible to do the talks in a virtual way.
List of Topics
The last two-year period has seen a impressive revolution in the theory and application of machine learning, optimization, artificial intelligence and big data. Topics of interest include, but are not limited to:
- Foundations, algorithms, models and theory of data science, including big data mining.
- Machine learning and statistical methods for big data.
- Machine Learning algorithms and models. Neural Networks and Learning Systems. Convolutional neural networks.
- Unsupervised, semi-supervised, and supervised Learning.
- Knowledge Discovery. Learning Representations. Representation learning for planning and reinforcement learning.
- Metric learning and kernel learning. Sparse coding and dimensionality expansion. Hierarchical models. Learning representations of outputs or states.
- Multi-objective optimization. Optimization and Game Theory. Surrogate-assisted Optimization. Derivative-free Optimization.
- Big data Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.
- Big Data mining systems and platforms, and their efficiency, scalability, security and privacy.
- Computational optimization. Optimization for representation learning. Optimization under Uncertainty
- Optimization algorithms for Real World Applications. Optimization for Big Data. Optimization and Machine Learning.
- Implementation issues, parallelization, software platforms, hardware
- Big Data mining for modeling, visualization, personalization, and recommendation.
- Big Data mining for cyber-physical systems and complex, time-evolving networks.
- Applications in social sciences, physical sciences, engineering, life sciences, web, marketing, finance, precision medicine, health informatics, medicine and other domains.
We particularly encourage submissions in emerging topics of high importance such as data quality, advanced deep learning, time-evolving networks, large multi-objective optimization, quantum discrete optimization, learning representations, big data mining and analytics, cyber-physical systems, heterogeneous data integration and mining, autonomous decision and adaptive control.
Committees
Program Committee (500+ confirmed PC members)
https://lod2021.icas.cc/program-committee/
Organizing committee
https://lod2021.icas.cc/committee/
Invited Speakers
https://lod2021.icas.cc/keynote/
Publication
LOD 2021 proceedings will be published in Springer Nature - Lecture Notes in Computer Science (LNCS).
We invite submissions of papers on all topics related to Machine learning, Optimization, Artificial Intelligence, Deep Learning, Big Data, Knowledge Discovery and Data Science including real-world applications for the Conference Post-Proceedings by Springer Nature – Lecture Notes in Computer Science (LNCS).
https://lod2021.icas.cc/call-for-papers/
Venue
The conference will be held in The Wordsworth Hotel & SPA in Grasmere – Lake District, England, UK
https://lod2021.icas.cc/venue/
Contact
All questions about submissions should be emailed to lod@icas.cc
Sponsors
https://lod2021.icas.cc/sponsors/