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» Simplifying Mixture Models Using the Unscented Transform
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IEICET
2008
93views more  IEICET 2008»
13 years 7 months ago
Compression Functions Suitable for the Multi-Property-Preserving Transform
Since Bellare and Ristenpart showed a multi-property preserving domain extension transform, the problem of the construction for multi-property hash functions has been reduced to th...
Hidenori Kuwakado, Masakatu Morii
ACL
2008
13 years 9 months ago
Sentence Simplification for Semantic Role Labeling
Parse-tree paths are commonly used to incorporate information from syntactic parses into NLP systems. These systems typically treat the paths as atomic (or nearly atomic) features...
David Vickrey, Daphne Koller
NIPS
2008
13 years 9 months ago
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
Simon Lacoste-Julien, Fei Sha, Michael I. Jordan
ICIP
2004
IEEE
14 years 9 months ago
Sparse representation of images with hybrid linear models
We propose a mixture of multiple linear models, also known as hybrid linear model, for a sparse representation of an image. This is a generalization of the conventional KarhunenLo...
Kun Huang, Allen Y. Yang, Yi Ma
ICDM
2006
IEEE
145views Data Mining» more  ICDM 2006»
14 years 1 months ago
Stability Region Based Expectation Maximization for Model-based Clustering
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...