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» Bayesian Inference for Sparse Generalized Linear Models
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NIPS
2003
15 years 3 months ago
Laplace Propagation
We present a novel method for approximate inference in Bayesian models and regularized risk functionals. It is based on the propagation of mean and variance derived from the Lapla...
Alexander J. Smola, Vishy Vishwanathan, Eleazar Es...
NIPS
2001
15 years 3 months ago
Bayesian morphometry of hippocampal cells suggests same-cell somatodendritic repulsion
Visual inspection of neurons suggests that dendritic orientation may be determined both by internal constraints (e.g. membrane tension) and by external vector fields (e.g. neurotr...
Giorgio A. Ascoli, Alexei V. Samsonovich
TIP
2010
255views more  TIP 2010»
14 years 8 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
FCT
2003
Springer
15 years 7 months ago
Graph Searching, Elimination Trees, and a Generalization of Bandwidth
The bandwidth minimization problem has a long history and a number of practical applications. In this paper we introduce a natural extension of bandwidth to partially ordered layo...
Fedor V. Fomin, Pinar Heggernes, Jan Arne Telle
PAMI
2012
13 years 4 months ago
Task-Driven Dictionary Learning
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...
Julien Mairal, Francis Bach, Jean Ponce