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ICML
2004
IEEE
16 years 4 months ago
Generalized low rank approximations of matrices
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
Jieping Ye
118
Voted
CORR
2008
Springer
114views Education» more  CORR 2008»
15 years 3 months ago
Network-based consensus averaging with general noisy channels
This paper focuses on the consensus averaging problem on graphs under general noisy channels. We study a particular class of distributed consensus algorithms based on damped updat...
Ram Rajagopal, Martin J. Wainwright
IJCNN
2007
IEEE
15 years 9 months ago
Optimizing 0/1 Loss for Perceptrons by Random Coordinate Descent
—The 0/1 loss is an important cost function for perceptrons. Nevertheless it cannot be easily minimized by most existing perceptron learning algorithms. In this paper, we propose...
Ling Li, Hsuan-Tien Lin
125
Voted
NIPS
2007
15 years 4 months ago
Topmoumoute Online Natural Gradient Algorithm
Guided by the goal of obtaining an optimization algorithm that is both fast and yields good generalization, we study the descent direction maximizing the decrease in generalizatio...
Nicolas Le Roux, Pierre-Antoine Manzagol, Yoshua B...
128
Voted
JACM
2000
131views more  JACM 2000»
15 years 3 months ago
The soft heap: an approximate priority queue with optimal error rate
A simple variant of a priority queue, called a soft heap, is introduced. The data structure supports the usual operations: insert, delete, meld, and findmin. Its novelty is to beat...
Bernard Chazelle