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» Learning to Align: A Statistical Approach
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NIPS
2008
13 years 10 months ago
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Guangzhi Cao, Charles A. Bouman
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
13 years 10 months ago
Cluster Ensemble Selection
This paper studies the ensemble selection problem for unsupervised learning. Given a large library of different clustering solutions, our goal is to select a subset of solutions t...
Xiaoli Z. Fern, Wei Lin
SDM
2008
SIAM
133views Data Mining» more  SDM 2008»
13 years 10 months ago
Semantic Smoothing for Bayesian Text Classification with Small Training Data
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu
NIPS
2007
13 years 10 months ago
Modeling Natural Sounds with Modulation Cascade Processes
Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences (∼1 s); phonemes (âˆ...
Richard Turner, Maneesh Sahani
AAAI
2004
13 years 10 months ago
Reconstruction of 3D Models from Intensity Images and Partial Depth
This paper addresses the probabilistic inference of geometric structures from images. Specifically, of synthesizing range data to enhance the reconstruction of a 3D model of an in...
Luz Abril Torres-Méndez, Gregory Dudek