Sciweavers

ICASSP
2011
IEEE
13 years 4 months ago
Compressed classification of observation sets with linear subspace embeddings
We consider the problem of classification of a pattern from multiple compressed observations that are collected in a sensor network. In particular, we exploit the properties of r...
Dorina Thanou, Pascal Frossard
PAMI
2011
13 years 7 months ago
Multiple Kernel Learning for Dimensionality Reduction
—In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. The resulting ...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
IVC
2007
184views more  IVC 2007»
14 years 9 days ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless
SBBD
2004
94views Database» more  SBBD 2004»
14 years 1 months ago
Visual Analysis of Feature Selection for Data Mining Processes
The amount of data collected in the last decades has become a source of valuable information, allowing organizations to improve their competitiveness. However, the associated data...
Humberto Luiz Razente, Fabio Jun Takada Chino, Mar...
APVIS
2010
14 years 1 months ago
GMap: Visualizing graphs and clusters as maps
Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
Emden R. Gansner, Yifan Hu, Stephen G. Kobourov
SLSFS
2005
Springer
14 years 5 months ago
Auxiliary Variational Information Maximization for Dimensionality Reduction
Abstract. Mutual Information (MI) is a long studied measure of information content, and many attempts to apply it to feature extraction and stochastic coding have been made. Howeve...
Felix V. Agakov, David Barber
PODS
2001
ACM
190views Database» more  PODS 2001»
15 years 16 days ago
On the Effects of Dimensionality Reduction on High Dimensional Similarity Search
The dimensionality curse has profound e ects on the effectiveness of high-dimensional similarity indexing from the performance perspective. One of the well known techniques for im...
Charu C. Aggarwal
SIGMOD
2001
ACM
184views Database» more  SIGMOD 2001»
15 years 17 days ago
Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases
Similarity search in large time series databases has attracted much research interest recently. It is a difficult problem because of the typically high dimensionality of the data....
Eamonn J. Keogh, Kaushik Chakrabarti, Sharad Mehro...
ECCV
2004
Springer
15 years 2 months ago
Transformation-Invariant Embedding for Image Analysis
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
Ali Ghodsi, Jiayuan Huang, Dale Schuurmans
ICCV
2003
IEEE
15 years 2 months ago
Image Spaces and Video Trajectories: Using Isomap to Explore Video Sequences
Dimensionality reduction techniques seek to represent a set of images as a set of points in a low dimensional space. Here we explore a video representation that considers a video ...
Robert Pless