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ISBI
2002
IEEE
15 years 4 months ago
Bayesian clustering methods for morphological analysis of MR images
Determining the relationship between structure (i.e. morphology) and function is a fundamental problem in brain research. In this paper we present a new framework based on Bayesia...
Hanchuan Peng, Edward Herskovits, Christos Davatzi...
97
Voted
DCC
2011
IEEE
14 years 6 months ago
Sparse Boolean equations and circuit lattices
Abstract. A system of Boolean equations is called sparse if each equation depends on a small number of variables. Finding efficiently solutions to the system is an underlying hard ...
Igor Semaev
ADCM
2007
104views more  ADCM 2007»
14 years 12 months ago
Shape preserving histogram approximation
We present a new method for reconstructing the density function underlying a given histogram. First we analyze the univariate case taking the approximating function in a class of q...
Paolo Costantini, Francesca Pelosi
DAC
2004
ACM
16 years 22 days ago
Refining the SAT decision ordering for bounded model checking
Bounded Model Checking (BMC) relies on solving a sequence of highly correlated Boolean satisfiability (SAT) problems, each of which corresponds to the existence of counter-example...
Chao Wang, HoonSang Jin, Gary D. Hachtel, Fabio So...
86
Voted
STOC
2003
ACM
122views Algorithms» more  STOC 2003»
16 years 2 days ago
Learning juntas
We consider a fundamental problem in computational learning theory: learning an arbitrary Boolean function which depends on an unknown set of k out of n Boolean variables. We give...
Elchanan Mossel, Ryan O'Donnell, Rocco A. Servedio