Category: workshop

New Challenges in Machine Learning – Robustness and Nonconvexity

~ shacharlovett

June 23, 2017
STOC 2017, Montreal, Canada
https://users.cs.duke.edu/~rongge/stoc2017ml/stoc2017ml.html

Submission deadline: May 27, 2017

Machine learning has gone through a major transformation in the last decade. Traditional methods based on convex optimization have been replaced by highly non-convex approaches including deep learning. In the worst-case, the underlying optimization problems are NP-hard. Therefore to understand their success, we need new tools to characterize properties of natural inputs, and design algorithms that work provably in beyond-worst-case settings. In particular, robustness and nonconvexity are two of the major challenges.

STOC’17 Workshop on TCS and Mechanism Design

~ shacharlovett

June 23, 2017
Montreal
https://www.cs.princeton.edu/~smattw/STOC17BMD/

Submission deadline: May 12, 2017
Registration deadline: May 21, 2017

Mechanism Design is a subarea at the intersection of economics and algorithms that has in recent years benefited tremendously from TCS-centric approaches and the TCS toolkit. The goals of this workshop are to highlight recent theoretical advances in mechanism design, and to provide an overview of current/future research directions that are accessible to TCS researchers. The workshop will focus on the following three themes: Learning and Mechanism Design; Duality in Mechanism Design; Simple versus Optimal Mechanisms.

We are soliciting posters on any topic related to mechanism design.

Northwestern Workshop on Beyond Worst Case Analysis

~ shacharlovett

May 24-25, 2017
Northwestern University, Evanston, IL
https://theory.eecs.northwestern.edu/bwca/

The workshop is on the theme of Beyond Worst-Case Analysis. The speakers will discuss various natural models of real-life instances, present new algorithms for these models, and talk about the limitations of these models.