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» Universal Sparse Modeling
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87
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ESANN
2007
15 years 2 months ago
Collaborative Filtering with interlaced Generalized Linear Models
Collaborative Filtering (CF) aims at finding patterns in a sparse matrix of contingency. It can be used for example to mine the ratings given by users on a set of items. In this p...
Nicolas Delannay, Michel Verleysen
130
Voted
ISBI
2011
IEEE
14 years 4 months ago
Sparse topological data recovery in medical images
For medical image analysis, the test statistic of the measurements is usually constructed at every voxels in space and thresholded to determine the regions of significant signals...
Moo K. Chung, Hyekyoung Lee, Peter T. Kim, Jong Ch...
104
Voted
NIPS
2004
15 years 2 months ago
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons
This paper explores the computational consequences of simultaneous intrinsic and synaptic plasticity in individual model neurons. It proposes a new intrinsic plasticity mechanism ...
Jochen Triesch
103
Voted
ICA
2004
Springer
15 years 6 months ago
Postnonlinear Overcomplete Blind Source Separation Using Sparse Sources
Abstract. We present an approach for blindly decomposing an observed random vector x into f(As) where f is a diagonal function i.e. f = f1 × . . . × fm with one-dimensional funct...
Fabian J. Theis, Shun-ichi Amari
76
Voted
ICANNGA
2009
Springer
141views Algorithms» more  ICANNGA 2009»
15 years 5 months ago
Connection Strategies in Associative Memory Models with Spiking and Non-spiking Neurons
The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real n...
Weiliang Chen, Reinoud Maex, Rod Adams, Volker Ste...