• Click on the titles of individual talks for abstract, slides and archived video.

–
Coffee and Check-In
–
Opening Remarks
–
Google's AdWords Market: How Theory Influenced Practice
Vijay Vazirani, UC Irvine
–
Break
–
Mechanism Design Beyond Risk Neutrality
Manolis Pountorakis, University of Texas at Austin
–
When Does Diversity of Agent Preferences Improve Outcomes in Selfish Routing
Evdokia Nikolova, University of Texas at Austin
–
Lunch
–
Predicting Intersection Signal Timing
Pravin Varaiya, UC Berkeley
–
Break
–
Rebalancing in Bike-Sharing Systems – Incentives and Other Stories
David Shmoys, Cornell University
–
A Dashboard for Cities to Manage Fleets
Damon Wischik, University of Cambridge
–
Coffee and Check-In
–
On Learning Graph Binomial Distributions and Powers of Poisson Binomial Distributions
Dimitris Fotakis, National Technical University of Athens & Yahoo
–
Break
–
Streaming Algorithms for Matchings in Low Arboricity Graphs
Sofya Vorotnikova, University of Massachusetts Amherst
–
Sparse Fourier Transform Algorithm for Real-Time Applications
Haitham Hassanieh, University of Illinois Urbana-Champaign
–
Lunch
–
Self-Programming Networks: Network Clock Synchronization, Event Playback and Real-time Action
Balaji Prabhakar, Stanford University
–
Break
–
Exact Minimum Number of Bits to Stabilize a Linear System
Victoria Kostina, California Institute of Technology
–
An Informational Perspective on Uncertainty in Control
Gireeja Ranade, Microsoft Research
–
Coffee and Check-In
–
Rerouting Flows when Links Fail
Jannik Matuschke, University of Munich
–
Break
–
Broadcasting on Directed Acyclic Graphs
Yury Polyanskiy, Massachusetts Institute of Technology
–
Practical Data-Dependent Metric Compression with Provable Guarantees
Piotr Indyk, Massachusetts Institute of Technology
–
Lunch
–
Learning What Works Best When
Swati Gupta, Georgia Institute of Technology
–
Reception
–
Coffee and Check-In
–
Regularization, Perturbations, and Stability in Online Learning
Ambuj Tewari, University of Michigan
–
Break
–
Limited Communication Gradient Methods for Distributed Resource Allocation Optimization
Na (Lina) Li, Harvard University
–
A Bayesian Approach to Online Resource Allocation
Sid Banerjee, Cornell University
–
Lunch
–
Mergeable Summaries and the Data Sketches Library
Edo Liberty, Amazon
–
Break
–
Provable Learning of Real-time Big Data Using Core-sets
Dan Feldman, University of Haifa
–
Towards Verification of General Neural Networks: A Dual Approach
Krishnamurthy Dvijotham, Deepmind
–
Coffee and Check-In
–
Relative Error Tensor Low Rank Approximation
David Woodruff, Carnegie Mellon University
–
Break
–
Integrating Functions via Distance Sensitive Hashing
Moses Charikar, Stanford University
–
Active Regression via Linear-Sample Sparsification
Eric Price, University of Texas at Austin