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» Metric and Kernel Learning Using a Linear Transformation
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NIPS
2008
15 years 3 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
106
Voted
BMCBI
2007
147views more  BMCBI 2007»
15 years 1 months ago
Comparative analysis of long DNA sequences by per element information content using different contexts
Background: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression mode...
Trevor I. Dix, David R. Powell, Lloyd Allison, Jul...
121
Voted
ESA
2008
Springer
111views Algorithms» more  ESA 2008»
15 years 3 months ago
Parallel Imaging Problem
Metric Labeling problems have been introduced as a model for understanding noisy data with pair-wise relations between the data points. One application of labeling problems with pa...
Thành Nguyen, Éva Tardos
ICASSP
2010
IEEE
15 years 2 months ago
HMM-based sequence-to-frame mapping for voice conversion
Voice conversion can be reduced to a problem to find a transformation function between the corresponding speech sequences of two speakers. Perhaps the most voice conversions meth...
Yu Qiao, Daisuke Saito, Nobuaki Minematsu
155
Voted
CVPR
2010
IEEE
15 years 6 months ago
The Automatic Design of Feature Spaces for Local Image Descriptors using an Ensemble of Non-linear Feature Extractors
The design of feature spaces for local image descriptors is an important research subject in computer vision due to its applicability in several problems, such as visual classifi...
Gustavo Carneiro