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» Optimization of Convex Risk Functions
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ICMLA
2009
13 years 7 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
CDC
2010
IEEE
181views Control Systems» more  CDC 2010»
13 years 4 months ago
Relationship between power loss and network topology in power systems
This paper is concerned with studying how the minimum power loss in a power system is related to its network topology. The existing algorithms in the literature all exploit nonline...
Javad Lavaei, Steven H. Low
TON
2010
162views more  TON 2010»
13 years 4 months ago
Fast Algorithms for Resource Allocation in Wireless Cellular Networks
Abstract--We consider a scheduled orthogonal frequency division multiplexed (OFDM) wireless cellular network where the channels from the base-station to the mobile users undergo fl...
Ritesh Madan, Stephen P. Boyd, Sanjay Lall
CORR
2011
Springer
167views Education» more  CORR 2011»
13 years 4 months ago
Fast global convergence of gradient methods for high-dimensional statistical recovery
Many statistical M-estimators are based on convex optimization problems formed by the weighted sum of a loss function with a norm-based regularizer. We analyze the convergence rat...
Alekh Agarwal, Sahand Negahban, Martin J. Wainwrig...
TIP
2008
127views more  TIP 2008»
13 years 9 months ago
SURE-LET Multichannel Image Denoising: Interscale Orthonormal Wavelet Thresholding
Abstract--We propose a vector/matrix extension of our denoising algorithm initially developed for grayscale images, in order to efficiently process multichannel (e.g., color) image...
Florian Luisier, Thierry Blu