263 citations · 358 across the 5 of their papers we have counts for
5 papers
Search-based Structured Prediction
Hal Daumé, John Langford, Daniel Marcu
We present Searn, an algorithm for integrating search and learning to solve complex structured prediction problems such as those that occur in natural language, speech, computation…
Learning Nonlinear Dynamic Models
John Langford, Ruslan Salakhutdinov, Tong Zhang
We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory sho…
Conditional Probability Tree Estimation Analysis and Algorithms
Alina Beygelzimer, John Langford, Yuri Lifshits +2
We consider the problem of estimating the conditional probability of a label in time , where is the number of possible labels. We analyze a natural reduction of this…
Multi-Label Prediction via Compressed Sensing
Daniel Hsu, Sham M. Kakade, John Langford +1
We consider multi-label prediction problems with large output spaces under the assumption of output sparsity -- that the target (label) vectors have small support. We develop a gen…
Importance Weighted Active Learning
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
We present a practical and statistically consistent scheme for actively learning binary classifiers under general loss functions. Our algorithm uses importance weighting to correct…