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CORR
2010
Springer
162views Education» more  CORR 2010»
15 years 3 months ago
Random sampling of lattice paths with constraints, via transportation
We investigate Monte Carlo Markov Chain (MCMC) procedures for the random sampling of some one-dimensional lattice paths with constraints, for various constraints. We will see that...
Lucas Gerin
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 7 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
118
Voted
OOPSLA
2010
Springer
15 years 1 months ago
Random testing for higher-order, stateful programs
Testing is among the most effective tools available for finding bugs. Still, we know of no automatic technique for generating test cases that expose bugs involving a combination ...
Casey Klein, Matthew Flatt, Robert Bruce Findler
GECCO
2006
Springer
195views Optimization» more  GECCO 2006»
15 years 7 months ago
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Recently, studies with the XCS classifier system on Boolean functions have shown that in certain types of functions simple crossover operators can lead to disruption and, conseque...
Martin V. Butz, Martin Pelikan
PAMI
2008
198views more  PAMI 2008»
15 years 3 months ago
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors
Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel-labeling tasks such as depth or texture computation....
Richard Szeliski, Ramin Zabih, Daniel Scharstein, ...