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SCIA
2009
Springer
305views Image Analysis» more  SCIA 2009»
13 years 11 months ago
A Convex Approach to Low Rank Matrix Approximation with Missing Data
Many computer vision problems can be formulated as low rank bilinear minimization problems. One reason for the success of these problems is that they can be efficiently solved usin...
Carl Olsson, Magnus Oskarsson
MMAS
2011
Springer
13 years 7 days ago
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems
While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and thei...
Phaedon-Stelios Koutsourelakis, Elias Bilionis
NIPS
2007
13 years 6 months ago
A neural network implementing optimal state estimation based on dynamic spike train decoding
It is becoming increasingly evident that organisms acting in uncertain dynamical environments often employ exact or approximate Bayesian statistical calculations in order to conti...
Omer Bobrowski, Ron Meir, Shy Shoham, Yonina C. El...
FGR
2006
IEEE
255views Biometrics» more  FGR 2006»
13 years 9 months ago
Incremental Kernel SVD for Face Recognition with Image Sets
Non-linear subspaces derived using kernel methods have been found to be superior compared to linear subspaces in modeling or classification tasks of several visual phenomena. Such...
Tat-Jun Chin, Konrad Schindler, David Suter
VLSID
2006
IEEE
129views VLSI» more  VLSID 2006»
14 years 5 months ago
A Stimulus-Free Probabilistic Model for Single-Event-Upset Sensitivity
With device size shrinking and fast rising frequency ranges, effect of cosmic radiations and alpha particles known as Single-Event-Upset (SEU), Single-Eventtransients (SET), is a ...
Mohammad Gh. Mohammad, Laila Terkawi, Muna Albasma...