186 citations · 186 across the 1 of their papers we have counts for
4 papers · 1 filter
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…
Sparse Online Learning via Truncated Gradient
John Langford, Lihong Li, Tong Zhang
We propose a general method called truncated gradient to induce sparsity in the weights of online learning algorithms with convex loss functions. This method has several essential…