We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
We show how the regularizer of Transductive Support Vector Machines (TSVM) can be trained by stochastic gradient descent for linear models and multi-layer architectures. The resul...
Michael Karlen, Jason Weston, Ayse Erkan, Ronan Co...
We consider a model of analog computation which can recognize various languages in real time. We encode an input word as a point in Rd by composing iterated maps, and then apply i...
This paper proposes a general learning framework for a class of problems that require learning over latent intermediate representations. Many natural language processing (NLP) dec...
Ming-Wei Chang, Dan Goldwasser, Dan Roth, Vivek Sr...
In this work, we present a new semantic language modeling approach to model news stories in the Topic Detection and Tracking (TDT) task. In the new approach, we build a unigram la...