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» Minimization of an M-convex Function
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JMLR
2010
147views more  JMLR 2010»
13 years 4 months ago
Image Denoising with Kernels Based on Natural Image Relations
A successful class of image denoising methods is based on Bayesian approaches working in wavelet representations. The performance of these methods improves when relations among th...
Valero Laparra, Juan Gutierrez, Gustavo Camps-Vall...
SIAMIS
2010
171views more  SIAMIS 2010»
13 years 4 months ago
Global Optimization for One-Dimensional Structure and Motion Problems
We study geometric reconstruction problems in one-dimensional retina vision. In such problems, the scene is modeled as a 2D plane, and the camera sensor produces 1D images of the s...
Olof Enqvist, Fredrik Kahl, Carl Olsson, Kalle &Ar...
SIAMJO
2010
130views more  SIAMJO 2010»
13 years 4 months ago
A Randomized Cutting Plane Method with Probabilistic Geometric Convergence
Abstract. We propose a randomized method for general convex optimization problems; namely, the minimization of a linear function over a convex body. The idea is to generate N rando...
Fabrizio Dabbene, P. S. Shcherbakov, Boris T. Poly...
SIGOPS
2010
179views more  SIGOPS 2010»
13 years 4 months ago
Online cache modeling for commodity multicore processors
Modern chip-level multiprocessors (CMPs) contain multiple processor cores sharing a common last-level cache, memory interconnects, and other hardware resources. Workloads running ...
Richard West, Puneet Zaroo, Carl A. Waldspurger, X...
TNN
2010
168views Management» more  TNN 2010»
13 years 4 months ago
On the selection of weight decay parameter for faulty networks
The weight-decay technique is an effective approach to handle overfitting and weight fault. For fault-free networks, without an appropriate value of decay parameter, the trained ne...
Andrew Chi-Sing Leung, Hongjiang Wang, John Sum