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MIA
2010
170views more  MIA 2010»
15 years 1 months ago
Linear intensity-based image registration by Markov random fields and discrete optimization
We propose a framework for intensity-based registration of images by linear transformations, based on a discrete Markov Random Field (MRF) formulation. Here, the challenge arises ...
Darko Zikic, Ben Glocker, Oliver Kutter, Martin Gr...
ALENEX
2001
101views Algorithms» more  ALENEX 2001»
15 years 7 months ago
CNOP - A Package for Constrained Network Optimization
Abstract. We present a generic package for resource constrained network optimization problems. We illustrate the flexibility and the use of our package by solving four applications...
Kurt Mehlhorn, Mark Ziegelmann
ACL
1994
15 years 7 months ago
Optimizing the Computational Lexicalization of Large Grammars
The computational lexicalization of a grammar is the optimization of the links between lexicalized rules and lexical items in order to improve the quality of the bottom-up filteri...
Christian Jacquemin
SIAMJO
2010
125views more  SIAMJO 2010»
15 years 1 months ago
Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints
We study the problem of minimizing the expected loss of a linear predictor while constraining its sparsity, i.e., bounding the number of features used by the predictor. While the r...
Shai Shalev-Shwartz, Nathan Srebro, Tong Zhang
APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 12 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál