ml-udm.github.io
Workshop on Machine Learning and User Decision Making
Dates: May 23-24, 2019
Venue: 29 rue d’Ulm, Paris, France (special note: access to registered attendees, not affiliated with ENS, will be through 24, rue Lhomond)
Organizers: Laurent Massoulie (MSR-INRIA Joint Centre) and Milan Vojnovic (London School of Economics)
Scope: The scope of this workshop is to discuss important algorithmic and mathematical questions that arise at the interface between machine learning and user decision making. The topics include but are not limited to online matching in uncertain environments, reinforcement learning, optimization and learning, mechanism design for online platforms, and recommender systems.
Please contact the organizers if you would like to attend.
Program schedule
Note: link to slides or papers are provided for some of the talks in __abstract__ pages
| Time | Day 1 - Thursday May 23, 2019 |
|---|---|
| 08:45- 09:00 |
Welcome note |
| 09:00- 09:55 |
Online Algorithms, Learning and Game Theory: Linear, Convex and Beyond Nikhil Devanur, Microsoft Research Abstract |
| 10:00- 10:55 |
Exploration in Structured Reinforcement Learning Alexandre Proutière, KTH Abstract |
| 11:00- 11:30 |
Coffee break |
| 11:30- 12:25 |
Can RL Learn Classic Optimization Algorithms Aranyak Mehta, Google Research Abstract |
| 12:30- 14:00 |
Lunch break |
| 14:00- 14:55 |
Optimal Control in Dynamic Matching Systems Ana Busic, INRIA Abstract |
| 15:00- 15:55 |
State Dependent Control of Ride-Hailing Systems Yash Kanoria, Columbia University Abstract |
| 16:00- 16:55 |
On The Limits and Potential Solutions for state-of-the-art Recommendation Flavian Vasile, Criteo Abstract |
| Time | Day 2 - Friday May 24, 2019 |
| 09:00- 09:55 |
On Reinforcement Learning using Monte Carlo Tree Search with Supervised Learning: Non-Asymptotic Analysis Devavrat Shah, MIT Abstract |
| 10:00- 10:55 |
Hierarchical Clustering Claire Mathieu, CNRS Abstract |
| 11:00- 11:30 |
Coffee break |
| 11:30- 12:25 |
Optimal Auctions through Deep Learning Paul Duetting, LSE Abstract |
| 12:30- 14:00 |
Lunch break |
| 14:00- 14:55 |
Adaptive Experimental Design with Temporal Interference Ramesh Johari, Stanford University Abstract |
| 15:00- 15:55 |
Econometrics and Machine Learning through the Lens of Neyman Orthogonality Vasilis Syrgkanis, Microsoft Research Abstract |
| 16:00- 16:55 |
Decision Theoretic Approach for Improved Training of Generative Adversarial Networks Sewoong Oh, University of Washington Abstract |