2.6k citations · 8.6k across the 77 of their papers we have counts for
5 papers · 1 filter
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…
Doubly Robust Policy Evaluation and Optimization
Miroslav Dudík, Dumitru Erhan, John Langford +1
We study sequential decision making in environments where rewards are only partially observed, but can be modeled as a function of observed contexts and the chosen action by the de…
Learning to Search for Dependencies
Kai-Wei Chang, He He, Hal Daumé +1
We demonstrate that a dependency parser can be built using a credit assignment compiler which removes the burden of worrying about low-level machine learning details from the parse…
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…
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…