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Spring School on Data Science, Machine Learning and Optimization

In conjunction with the International Symposium on Combinatorial Optimization (ISCO 2020)

Saturday and Sunday, May 2-3, 2020

Montreal, Canada

In today's world, Machine Learning and Mathematical Optimization lie at the heart of many of the decisions that affect society, individuals and the environment. While these fields developed somewhat independently, the last decade has seen considerable interest, from both research communities, in bringing machine learning and mathematical optimization closer together. This closer relationship has lead to new perspectives and methods in both fields, including:

• New continuous optimization methods for deep learning;
• Machine learning driven algorithms for combinatorial optimization;
• New principled optimization algorithms for constrained machine learning problems;
• Integration of predictive (machine learning) and prescriptive (optimization) modeling;
• Better sequential decision-making with deep reinforcement learning.

In parallel, a wide variety of application domains have benefited from the integration of learning and optimization.

The aim of the "Spring School on Data Science, Machine Learning and Optimization" is to introduce junior researchers to foundations and recent advances in some major areas of machine learning and mathematical optimization.

The School will be held in Montreal, Canada, on Saturday and Sunday, May 2-3, 2020, and in conjunction with the International Symposium on Combinatorial Optimization (ISCO 2020).

Each of the two days will feature a set of four 90-minute tutorial talks, two in the morning and two in the afternoon, for a total of eight tutorials by experts from both fields.

Registration:

Please register at the ISCO 2020 website at this link. You may register for both the conference and the Spring School or just the Spring School.

Location:

The Spring School will take place at HEC Montréal, 3000, chemin de la Côte-Sainte-Catherine, Montréal (Québec), Canada H3T 2A7.

Maps and instructions on how to get there are available at the ISCO 2020 webpage.

Speakers:

	Bistra Dilkina WiSE Gabilan Assistant Professor Department of Computer Science University of Southern California
	Ioannis Mitliagkas Assistant Professor Department of Computer Science and Operations Research University of Montreal Core Member, MILA CIFAR AI Chair
	Yossiri Adulyasak Canada Research Chair in Supply Chain Analytics Assistant Professor Department of Logistics and Operations Management HEC Montréal
	Elias B. Khalil IVADO Postdoctoral Scholar, Polytechnique Montreal Assistant Professor, Department of Mechanical & Industrial Engineering University of Toronto
	Maxime Gasse Postdoctoral Fellow Canada Excellence Research Chair in Data Science for Real-Time Decision-Making Polytechnique Montreal
	Chi-Guhn Lee Professor Department of Mechanical & Industrial Engineering University of Toronto
	Willem-Jan Van Hoeve Carnegie Bosch Professor of Operations Research Tepper School of Business Carnegie Mellon University
	Rahul Mazumder Robert G. James Career Development Associate Professor Operations Research and Statistics group MIT Sloan School of Management