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NIPS
2008
13 years 6 months ago
Structured ranking learning using cumulative distribution networks
Ranking is at the heart of many information retrieval applications. Unlike standard regression or classification in which we predict outputs independently, in ranking we are inter...
Jim C. Huang, Brendan J. Frey
PKDD
2010
Springer
178views Data Mining» more  PKDD 2010»
13 years 3 months ago
Large-Scale Support Vector Learning with Structural Kernels
Abstract. In this paper, we present an extensive study of the cuttingplane algorithm (CPA) applied to structural kernels for advanced text classification on large datasets. In par...
Aliaksei Severyn, Alessandro Moschitti
ICML
2007
IEEE
14 years 6 months ago
Incremental Bayesian networks for structure prediction
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
Ivan Titov, James Henderson
TSP
2010
13 years 1 hour ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...
ACL
2011
12 years 9 months ago
A Large Scale Distributed Syntactic, Semantic and Lexical Language Model for Machine Translation
This paper presents an attempt at building a large scale distributed composite language model that simultaneously accounts for local word lexical information, mid-range sentence s...
Ming Tan, Wenli Zhou, Lei Zheng, Shaojun Wang