Advances in ML: Theory meets practice
13:30-16:30 January 27

½ day
Intermediate level

Details

Efficient algorithms are indispensable in large scale ML applications. In recent years, the ML community has not just been a large consumer of what the optimization literature had to offer, but it has also been acting as a driving force in the development of new algorithmic tools. The challenges of massive data and efficient implementations have led to many cutting-edge advances in optimization.


The goal of this workshop is to bring practitioners and theoreticians together and to stimulate the exchange between experts from industry and academia. For practitioners, the workshop should give an idea of exciting new developments which they can *use* in their work. For theorists, it should provide a forum to frame the practicality of assumptions and recent work, as well as potentially interesting open questions.


Outcome

The stated goal is to bring practitioners and theory experts together, and to stimulate exchanges from both sides. For practitioners, the workshop should give an idea of exciting new developments which they can *use* in their work. For theorists, it should provide a forum to frame the practicality of assumptions and recent work, as well as potentially interesting open questions.


Prerequisites

The workshop will not discuss high level aspects of ML or data processing, but rather focus on core components that are essential for actual implementations. Hence, the participants should ideally be familiar with the main optimization algorithms used in ML and the main challenges arising in the implementations.

Organizers

Sebastian Stich

Scientist, EPFL

Website

Aymeric Dieuleveut

PostDoc, EPFL

Website