758 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Microsoft (United States)US53 papers
- Cornell UniversityUS15 papers
- Carnegie Mellon UniversityUS9 papers
- University of Massachusetts AmherstUS8 papers
- Princeton UniversityUS7 papers
- Columbia UniversityUS6 papers
- Microsoft Research (United Kingdom)GB6 papers
- University of PennsylvaniaUS6 papers
- University of Maryland, College ParkUS5 papers
- University of MichiganUS5 papers
- Harvard UniversityUS4 papers
- Stanford UniversityUS4 papers
13 papers · 1 filter
Rate of Price Discovery in Iterative Combinatorial Auctions
Jacob Abernethy, Sébastien Lahaie, Matus Telgarsky
We study a class of iterative combinatorial auctions which can be viewed as subgradient descent methods for the problem of pricing bundles to balance supply and demand. We provide…
Estimating the Causal Impact of Recommendation Systems from Observational Data
Amit Sharma, Jake M. Hofman, Duncan J. Watts
Recommendation systems are an increasingly prominent part of the web, accounting for up to a third of all traffic on several of the world's most popular sites. Nevertheless, little…
Pseudo-Query Reformulation
Fernando Diaz
Automatic query reformulation refers to rewriting a user's original query in order to improve the ranking of retrieval results compared to the original query. We present a general…
No-Regret Learning in Bayesian Games
Jason Hartline, Vasilis Syrgkanis, Eva Tardos
Recent price-of-anarchy analyses of games of complete information suggest that coarse correlated equilibria, which characterize outcomes resulting from no-regret learning dynamics,…
Fast Convergence of Regularized Learning in Games
Vasilis Syrgkanis, Alekh Agarwal, Haipeng Luo +1
We show that natural classes of regularized learning algorithms with a form of recency bias achieve faster convergence rates to approximate efficiency and to coarse correlated equi…
Efficient and Parsimonious Agnostic Active Learning
Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu +2
We develop a new active learning algorithm for the streaming setting satisfying three important properties: 1) It provably works for any classifier representation and classificatio…
Orbiting Radiation Stars
Dean P. Foster, John Langford, Gabe Perez-Giz
We study a numerical solution to Einstein's equation for a compact object composed of null particles. The solution avoids quantum scale regimes and hence neither relies upon nor ig…
Public Transit Labeling
Daniel Delling, Julian Dibbelt, Thomas Pajor +1
We study the journey planning problem in public transit networks. Developing efficient preprocessing-based speedup techniques for this problem has been challenging: current approac…
Econometrics for Learning Agents
Denis Nekipelov, Vasilis Syrgkanis, Eva Tardos
The main goal of this paper is to develop a theory of inference of player valuations from observed data in the generalized second price auction without relying on the Nash equilibr…
Incentivizing High Quality Crowdwork
Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri +1
We study the causal effects of financial incentives on the quality of crowdwork. We focus on performance-based payments (PBPs), bonus payments awarded to workers for producing high…
Learning Reductions that Really Work
Alina Beygelzimer, Hal Daumé, John Langford +1
We provide a summary of the mathematical and computational techniques that have enabled learning reductions to effectively address a wide class of problems, and show that this appr…
Contextual Semibandits via Supervised Learning Oracles
Akshay Krishnamurthy, Alekh Agarwal, Miroslav Dudik
We study an online decision making problem where on each round a learner chooses a list of items based on some side information, receives a scalar feedback value for each individua…
Learning to Search Better Than Your Teacher
Kai-Wei Chang, Akshay Krishnamurthy, Alekh Agarwal +2
Methods for learning to search for structured prediction typically imitate a reference policy, with existing theoretical guarantees demonstrating low regret compared to that refere…