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NIPS
2008
15 years 7 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
EGITALY
2006
15 years 7 months ago
3D Data Segmentation Using a Non-Parametric Density Estimation Approach
In this paper, a new segmentation approach for sets of 3D unorganized points is proposed. The method is based on a clustering procedure that separates the modes of a non-parametri...
Umberto Castellani, Marco Cristani, Vittorio Murin...
NIPS
2004
15 years 7 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...
VCIP
2000
15 years 7 months ago
Optimal down-conversion in compressed DCT domain with minimal operations
A new down-conversion scheme in the DCT domain is presented, which can be used in decoders of DCT-compressed images and videos. The down-conversion in the transform domain general...
Myoung-Cheol Shin, In-Cheol Park
MVA
1996
100views Computer Vision» more  MVA 1996»
15 years 7 months ago
Range Data Segmentation with Principal Vectors and Surface Types
A new method for segmenting range data including curved surfaceisproposed.Themethod isbasedonrobust principal vectors calculation using ISL-primary-axis method. First a normal vec...
Takashi Yoshimi, Yoshihiro Kawai, Fumiaki Tomita