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NIPS
2001
15 years 4 months ago
A General Greedy Approximation Algorithm with Applications
Greedy approximation algorithms have been frequently used to obtain sparse solutions to learning problems. In this paper, we present a general greedy algorithm for solving a class...
T. Zhang
UAI
2001
15 years 4 months ago
Maximum Likelihood Bounded Tree-Width Markov Networks
We study the problem of projecting a distribution onto (or finding a maximum likelihood distribution among) Markov networks of bounded tree-width. By casting it as the combinatori...
Nathan Srebro
120
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DISOPT
2006
90views more  DISOPT 2006»
15 years 3 months ago
Tree decompositions of graphs: Saving memory in dynamic programming
We propose an effective heuristic to save memory in dynamic programming on tree decompositions when solving graph optimization problems. The introduced "anchor technique"...
Nadja Betzler, Rolf Niedermeier, Johannes Uhlmann
112
Voted
NECO
2007
107views more  NECO 2007»
15 years 2 months ago
Training a Support Vector Machine in the Primal
Most literature on Support Vector Machines (SVMs) concentrate on the dual optimization problem. In this paper, we would like to point out that the primal problem can also be solve...
Olivier Chapelle
138
Voted
CORR
2011
Springer
214views Education» more  CORR 2011»
14 years 7 months ago
Convex Approaches to Model Wavelet Sparsity Patterns
Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as d...
Nikhil S. Rao, Robert D. Nowak, Stephen J. Wright,...