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<p>The LOD 2019 sponsor, Neodata Lab, will offer a prize of €2000 to the applicant who develops the most accurate algorithm to process an “approximate SQL-like query answering system” on a real dataset.
In order to participate to this contest (or if you have any inquire about the challenge) please send an email to the following address:
lod2019challenge@neodatagroup.com</p>
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<div style="font-family: arial; font-style: normal; font-variant-caps: normal; font-size: 14px; caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><strong><em>The 5th International Conference on machine Learning, Optimization & Data science - LOD<br>
An Interdisciplinary Conference: Deep Learning, Optimization and Big Data without Borders<br>
<br>
Certosa di Pontignano (Siena) Tuscany, September 10-13, 2019</em></strong></div>
<div style="font-family: arial; font-style: normal; font-variant-caps: normal; font-size: 14px; caret-color: rgb(0, 0, 0); color: rgb(0, 0, 0);"><strong><em> <a href="https://u9436285.ct.sendgrid.net/wf/click?upn=d4vXn57GZxbFUmLoz1hVorTHC85It5E28bAY-2FSXWCUM-3D_GA3tWWLb1-2FLi-2BYT1t27j3GdrqAbJ7ujJhf7xt0kVMkAmJXbUutw-2BCoEt8jH-2F-2Fe7ZiJaM-2BEQyAMeIHJeRiBQL8sCgzsRnFZ-2FvEh-2FH1TkJJhUKB1uUm1mjnej11c7uexAY2tacGO07aO-2FP7AVqD9j2RTK3-2F3P4CC6b-2FkZgg5IYEVPj-2BttMpBoBjk0ccgkOY99uPYLDs1XkGRyXM9vIK01hshBjbKJx4bfPaunwh3Gmq5q8mZ2TEojeXSpgUSouG5aCt3MwTTz3hz3dV2Mv3hkvV6wx5Im-2BuIx1WBmYtj41M6kCv4hHD7KugnixXF78h8dlYVHlnSSR8AgmEY-2FFAurCw7KRpQuDiVY43KeozIHomK4EZqvKp0Op8u4vlemXiiWzwJk1UUb3P-2BQ-2B-2FpbzoBXjzFBHenaxG0hdQHjX74c-2F44yx0IBS9wA6wilH0cM82K7urlEMcL5ycbVaUBsS2eoKHpscJqjbyfMU3573PLUSjEk-3D">https://lod2019.icas.xyz</a><br>
<a href="mailto:lod@icas.xyz?subject=LOD%202019&body=LOD%202019">lod@icas.xyz</a></em></strong></div>
<h1 style="text-align: left;">LOD 2019 Industrial Session</h1>
<div style="text-align: left;">As companies today are becoming more and more "data driven", this year we introduced an Industrial Session to encourage both researchers and companies to interact with each other. The basic idea is to create an environment where companies may present their vision, approach and issues on Big Data related topics, while researchers may be better tailor their results for the industrial need.</div>
<div style="text-align: left;">Thus we encourage both researchers and companies to submit original papers on issues that mostly cover, but are not limited to, areas such as:</div>
<ul>
<li style="text-align: left;"> Real industrial Big Data/AI based use cases</li>
<li style="text-align: left;"> Big Data solutions</li>
<li style="text-align: left;"> Industrial applications</li>
</ul>
<div style="text-align: left;">Furthermore, participating companies may apply for a 10-min oral talk to present their Big Data related issues (no paper submission is required for this activity). Following these presentations, ad-hoc meetings will be encouraged and organized by LOD itself between companies and researchers to address specific company issues. The idea is just to create a unique environment where companies discuss their Big Data issues with researchers in order to identify solutions for their problems. And, at the same time, offer to researchers the opportunity to develop new algorithms and solutions for Big Data real problems.</div>
<div style="text-align: left;"> </div>
<h1 style="text-align: left;">Big-Data Challenge</h1>
<div style="text-align: left;">Our sponsor, <strong>Neodata Lab, will offer a prize of €2000 t</strong>o the applicant who develops the most accurate algorithm to process an “approximate SQL-like query answering system” on a real dataset.</div>
<div style="text-align: left;"> </div>
<div style="text-align: left;">In order to participate to this contest (or if you have any inquire about the challenge) please send an email to the following address: </div>
<div style="text-align: left;"> </div>
<div style="text-align: left;"> <a href="mailto:lod2019challenge@neodatagroup.com?subject=LOD%202019%20Industrial%20Session&body=LOD%202019%20Industrial%20Session">lod2019challenge@neodatagroup.com</a></div>
<div style="text-align: left;"> </div>
<div style="text-align: left;">specifying your full name and affiliation. We will contact you with directions on how to download sample data.</div>
<div style="text-align: left;">All applicants will be given a link to download a real large encrypted dataset. The dataset is composed of two tables, one USER table with about 60M unique user ids and an ACTION table with a total of about 600M rows. Both tables are given in a tab separated format. The USER table is about 2.2Gb while the action table is about 35Gb.</div>
<div style="text-align: left;"> </div>
<div style="text-align: left;">The applicants are required to develop an algorithm to provide an approximate answer to a "SQL-like GROUP BY" query in a given time-frame (a few seconds/minutes). Basically, a query should run for <u>no longer than</u>the given time-frame and should return the best approximations for the specified counters.</div>
<div style="text-align: left;">During the conference a new sample of data will be used to test all participating algorithms.</div>
<div style="text-align: left;">The winner is the algorithm who provides the most accurate answer in the given time-frame.</div>
<div> </div>
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<div style="text-align: center;">LOD 2019 Call for Papers, Submission Deadline Approaching: March 31.</div>
<div style="text-align: center;"> </div>
<div style="text-align: center;">The 5th International Conference on machine Learning, Optimization & Data science - LOD</div>
<div style="text-align: center;"> </div>
<div style="text-align: center;">An Interdisciplinary Conference: Deep Learning, Optimization and Big Data without Borders<br>
<br>
Certosa di Pontignano (Siena) Tuscany, September 10-13, 2019</div>
<div style="text-align: center;"> https://lod2019.icas.xyz<br>
lod@icas.xyz</div>
<div> </div>
<div>*** Paper submission deadline approaching: March 31 ***<br>
<br>
The International Conference on Machine Learning, Optimization, and Data Science (LOD) has established itself as a premier interdisciplinary conference in machine learning, computational optimization, knowledge discovery and data science. It provides an international forum for presentation of original multidisciplinary research results, as well as exchange and dissemination of innovative and practical development experiences.<br>
LOD 2019 will be held in Certosa di Pontignano (Siena) – Tuscany, Italy, from September 10 to 13, 2019. </div>
<div>The conference will consist of four days of conference sessions. We invite submissions of papers on all topics related to Machine learning, Optimization, Knowledge Discovery and Data Science including real-world applications for the Conference Proceedings by Springer – Lecture Notes in Computer Science (LNCS).<br>
LOD uses the formula of 30 minutes presentations for fruitful exchanges between authors and participants.</div>
<div>Submission deadline: March 31, 2019<br>
https://easychair.org/conferences/?conf=lod2019<br>
Any questions regarding the submission process can be sent to conference organizers: lod@icas.xyz</div>
<div><br>
LOD 2019 KEYNOTE SPEAKERS<br>
===========<br>
* Michael Bronstein, Imperial College London, UK<br>
Talk: TBA<br>
Topics: Deep Learning on Graphs and Manifolds</div>
<div>* Marco Gori, University of Siena, Italy<br>
Talk: TBA<br>
Topics: Constraint-Based Approaches to Machine Learning</div>
<div>* Arthur Gretton, UCL, UK <br>
Talk: TBA<br>
Topics: Kernel Methods to Reveal Properties and Relations in Data</div>
<div>* Arthur Guez Google DeepMind, London, UK<br>
Talk: TBA<br>
Topics: General Reinforcement Learning Algorithms</div>
<div>* Kaisa Miettinen, University of Jyväskylä, Finland<br>
Talk: TBA<br>
Topics: Multiobjective Optimization & Decision Analytics</div>
<div>* Jan Peters, Technische Universitaet Darmstadt<br>
Talk: Machine Learning of Robot Skills</div>
<div>* Mauricio Resende, Amazon, USA<br>
Talk: TBA<br>
Topics: Combinatorial Optimization & Heuristics</div>
<div>* Richard E. Turner, University of Cambridge, UK<br>
Talk: TBA<br>
Topics: Gaussian Processes & Computer Perception</div>
<div>LOD 2019 Best Paper Award<br>
===============<br>
Springer sponsors the LOD 2019 Best Paper Award with a cash prize of EUR 1,000.<br>
The Award will be conferred at the conference on the authors of the best paper award.<br>
https://lod2019.icas.xyz/best-paper-award/</div>
<div><br>
Topics of Interest<br>
===============<br>
The last five-year period has seen an impressive revolution in the theory and application of machine learning, optimization and big data. </div>
<div>Topics of interest include, but are not limited to:<br>
* Deep Learning<br>
* Reinforcement Learning<br>
* Deep NeuroEvolution<br>
* Multi-Objective Optimization<br>
* Foundations, algorithms, models and theory of data science, including big data mining.<br>
* Machine learning and statistical methods for big data.<br>
* Machine Learning algorithms and models. Neural Networks and Learning Systems. Convolutional neural networks.<br>
* Unsupervised, semi-supervised, and supervised Learning.<br>
* Knowledge Discovery. Learning Representations. Representation learning for planning and reinforcement learning.<br>
* Metric learning and kernel learning. Sparse coding and dimensionality expansion. Hierarchical models. Learning representations of outputs or states.<br>
* Multi-objective optimization. Optimization and Game Theory. Surrogate-assisted Optimization. Derivative-free Optimization.<br>
* Big data Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data.<br>
* Big Data mining systems and platforms, and their efficiency, scalability, security and privacy.<br>
* Computational optimization. Optimization for representation learning. Optimization under Uncertainty<br>
* Optimization algorithms for Real World Applications. Optimization for Big Data. Optimization and Machine Learning.<br>
* Implementation issues, parallelization, software platforms, hardware<br>
* Big Data mining for modeling, visualization, personalization, and recommendation.<br>
* Big Data mining for cyber-physical systems and complex, time-evolving networks.<br>
* Applications in social sciences, physical sciences, engineering, life sciences, web, marketing, finance, precision medicine, health informatics, medicine and other domains.</div>
<div>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.</div>
<div> </div>
<div>Call for Papers:<br>
Submission deadline: March 31, 2019<br>
https://easychair.org/conferences/?conf=lod2019<br>
https://lod2019.icas.xyz/call-for-papers/</div>
<div><br>
See you in Siena!<br>
LOD 2019 Organizing Committee.</div>
<div><br>
https://lod2019.icas.xyz<br>
lod@icas.xyz</div>
<div>https://www.facebook.com/groups/2236577489686309/</div>
<div>https://www.linkedin.com/groups/12092025/</div>
<div>https://twitter.com/TaoSciences</div>
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