In structured prediction problems, outputs are not confined to binary labels; they are often complex objects such as sequences, trees, or alignments. Support Vector Machine (SVM) ...
We address the problem of learning the mapping between words and their possible pronunciations in terms of sub-word units. Most previous approaches have involved generative modeli...
We propose a formulation of the Decision Tree learning algorithm in the Compression settings and derive tight generalization error bounds. In particular, we propose Sample Compres...
Sauer's Lemma is extended to classes HN of binary-valued functions h on [n] = {1, . . . , n} which have a margin less than or equal to N on all x [n] with h(x) = 1, where th...
Inspired by co-training, many multi-view semi-supervised kernel methods implement the following idea: find a function in each of multiple Reproducing Kernel Hilbert Spaces (RKHSs)...