Previous work on Natural Language Processing for Information Retrieval has shown the inadequateness of semantic and syntactic structures for both document retrieval and categoriza...
We propose a new family of latent variable models called max-margin min-entropy (m3e) models, which define a distribution over the output and the hidden variables conditioned on ...
Kevin Miller, M. Pawan Kumar, Benjamin Packer, Dan...
This paper describes a hybrid model that combines machine learning with linguistic heuristics for integrating unknown word identification with Chinese word segmentation. The model...
In this paper, we define a family of syntactic kernels for automatic relational learning from pairs of natural language sentences. We provide an efficient computation of such mode...
We propose a general framework for support vector machines (SVM) based on the principle of multi-objective optimization. The learning of SVMs is formulated as a multiobjective pro...