Sciweavers

NECO
2010
154views more  NECO 2010»
13 years 3 months ago
Role of Homeostasis in Learning Sparse Representations
Neurons in the input layer of primary visual cortex in primates develop edge-like receptive fields. One approach to understanding the emergence of this response is to state that ...
Laurent U. Perrinet
ICIAR
2010
Springer
13 years 3 months ago
Face Recognition from Color Images Using Sparse Projection Analysis
The paper presents a novel feature extraction technique for face recognition which uses sparse projection axes to compute a lowdimensional representation of face images. The propos...
Vitomir Struc, Nikola Pavesic
CORR
2008
Springer
161views Education» more  CORR 2008»
13 years 3 months ago
Compressed Sensing of Analog Signals
Abstract--A traditional assumption underlying most data converters is that the signal should be sampled at a rate exceeding twice the highest frequency. This statement is based on ...
Yonina C. Eldar
PAMI
1998
197views more  PAMI 1998»
13 years 4 months ago
Inference of Integrated Surface, Curve, and Junction Descriptions From Sparse 3D Data
—We are interested in descriptions of 3D data sets, as obtained from stereo or a 3D digitizer. We therefore consider as input a sparse set of points, possibly associated with cer...
Chi-Keung Tang, Gérard G. Medioni
MOC
2002
149views more  MOC 2002»
13 years 4 months ago
Sparse squares of polynomials
We answer a question left open in an article of Coppersmith and Davenport which proved the existence of polynomials whose powers are sparse, and in particular polynomials whose squ...
John Abbott
SIAMJO
2008
108views more  SIAMJO 2008»
13 years 5 months ago
Sparse SOS Relaxations for Minimizing Functions that are Summations of Small Polynomials
This paper discusses how to find the global minimum of functions that are summations of small polynomials ("small" means involving a small number of variables). Some spa...
Jiawang Nie, James Demmel
NECO
2008
129views more  NECO 2008»
13 years 5 months ago
Sparse Coding via Thresholding and Local Competition in Neural Circuits
While evidence indicates that neural systems may be employing sparse approximations to represent sensed stimuli, the mechanisms underlying this ability are not understood. We desc...
Christopher J. Rozell, Don H. Johnson, Richard G. ...
CORR
2007
Springer
198views Education» more  CORR 2007»
13 years 5 months ago
Clustering and Feature Selection using Sparse Principal Component Analysis
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
Ronny Luss, Alexandre d'Aspremont
COMPUTING
2006
119views more  COMPUTING 2006»
13 years 5 months ago
Sparse Grids, Adaptivity, and Symmetry
Sparse grid methods represent a powerful and efficient technique for the representation and approximation of functions and particularly the solutions of partial differential equat...
Harry Yserentant
CORR
2010
Springer
136views Education» more  CORR 2010»
13 years 5 months ago
Optimally Sparse Frames
Frames have established themselves as a means to derive redundant, yet stable decompositions of a signal for analysis or transmission, while also promoting sparse expansions. Howe...
Peter G. Casazza, Andreas Heinecke, Felix Krahmer,...