Tuesday, 17 Nov 2015

09:35am - 09:50am

Registration

09:50am - 10:00am

Opening Remarks

10:00am - 10:50am

Efficient optimal strategies for adversarial linear regression (PDF)
Peter Bartlett, University of California at Berkeley, USA

10:50am - 11:20am

--- Group Photo & Coffee Break ---

11:20am - 12:10pm

Online learning with feedback graphs (PDF)
Nicolo Cesa-Bianchi, Università degli Studi di Milano, Italy

12.10pm - 02:00pm

--- Lunch Break ---

02:00pm - 02:50pm

Beyond equilibrium selection: average case analysis of game dynamics (PDF)
Georgios Piliouras, Singapore University of Technology and Design

02:50pm - 03:40pm

Adaptive data analysis without overfitting (PDF)
Vitaly Feldman, IBM, USA

03:40pm - 04:10pm

--- Coffee Break ---

04:10pm - 05:00pm

Active learning from single and multiple annotators (PDF)
Kamalika Chaudhuri, University of California at San Diego, USA

06:30pm - 07:30pm

Public Lecture: Turning (big) Data into (even better) Decisions

Speaker: Assaf Zeevi, Columbia University, USA

Venue: NUS University Hall Auditorium
Lee Kong Chian Wing, Level 2, 21 Lower Kent Ridge Road, Singapore 119077

Wednesday, 18 Nov 2015

09:45am - 10:00am

Registration

10:00am - 10:50am

New approaches to learn with probability measures using regularized optimal transport
Marco Cuturi, Kyoto University, Japan

10:50am - 11:20am

--- Coffee Break ---

11:20am - 12:10pm

Learning the uncertainty in robust Markov decision processes (PDF)
Xu Huan, National University of Singapore

12.10pm - 02:00pm

--- Lunch Break ---

02:00pm - 02:50pm

New results on bandit learning
Ohad Shamir, Weizmann Institute of Science, Israel

02:50pm - 03:40pm

On the robustness of learning in games with stochastically perturbed payoff observations (PDF)
Mario Bravo, Universidad de Santiago de Chile, Chile

03:40pm - 04:10pm

--- Coffee Break ---

04:10pm - 05:00pm

On connections between supervised learning and property elicitation, and on ranking from pairwise comparisons (PDF)
Shivani Agarwal, Indian Institute of Science, India and Harvard University, USA

Thursday, 19 Nov 2015

09:45am - 10:00am

Registration

10:00am - 10:50am

Empirical methods for control and optimization (PDF)
Rahul Jain, University of Southern California, USA

10:50am - 11:20am

--- Coffee Break ---

11:20am - 12:10pm

Learning and convergence to Nash in network games (PDF)
Mathieu Faure, GREQAM - Centre de la vieille Charité, France

12.10pm - 02:00pm

--- Lunch Break ---

02:00pm - 02:50pm

Convex bandits
Sébastien Bubeck, Microsoft Research, USA

02:50pm - 03:40pm

Partial monitoring with gaussian payoffs and side observations (PDF)
Csaba Szepesvári, University of Alberta, Canada

03:40pm - 04:10pm

--- Coffee Break ---

04:10pm - 05:00pm

Adaptive online learning for games, optimization and deviation bounds (PDF)
Karthik Sridharan, Cornell University, USA

06:30pm

Dinner (Volunteer and self-paid)

Venue: Penang Place, 1 Fusionopolis Way, Connexis #B1-20/24, Singapore 138632

Friday, 20 Nov 2015

09:45am - 10:00am

Registration

10:00am - 10:50am

Imitation dynamics and dominated strategies (PDF)
Yannick Viossat, Université Paris Dauphine, France

10:50am - 11:20am

--- Coffee Break ---

11:20am - 12:10pm

Learning in unprofitable games (PDF)
Josef Hofbauer, University of Vienna, Austria

12.10pm - 02:00pm

--- Lunch Break ---

02:00pm - 02:50pm

Online boosting algorithms (PDF)
Satyen Kale, Yahoo! Labs, USA

02:50pm - 03:40pm

On the equivalence of simulated annealing and interior point path following for optimization (PDF)
Jacob Abernethy, University of Michigan, USA

03:40pm - 04:10pm

--- Coffee Break ---

04:10pm - 04:40pm

Learning in repeated auctions (PDF)
Jonathan Weed, Massachusetts Institute of Technology, USA

04:40pm - 05:10pm

Gains and losses are fundamentally different in regret minimization. The sparse case. (PDF)
Joon Kwon, University Pierre and Marie Curie, France