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» Optimizing Local Probability Models for Statistical Parsing
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CEC
2010
IEEE
13 years 8 months ago
Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails
Abstract-- Recently, the research on quantum-inspired evolutionary algorithms (QEA) has attracted some attention in the area of evolutionary computation. QEA use a probabilistic re...
Hui Li, Dario Landa Silva, Xavier Gandibleux
NIPS
1994
13 years 9 months ago
Active Learning with Statistical Models
For many types of machine learning algorithms, one can compute the statistically optimal" way to select training data. In this paper, we review how optimal data selection tec...
David A. Cohn, Zoubin Ghahramani, Michael I. Jorda...
IPMI
2007
Springer
14 years 8 months ago
A Shape-Guided Deformable Model with Evolutionary Algorithm Initialization for 3D Soft Tissue Segmentation
Abstract. We present a novel method for the segmentation of volumetric images, which is especially suitable for highly variable soft tissue structures. Core of the algorithm is a s...
Hans-Peter Meinzer, Ivo Wolf, Sascha Münzing,...
MICCAI
2004
Springer
14 years 8 months ago
Segmentation of 3D Probability Density Fields by Surface Evolution: Application to Diffusion MRI
We propose an original approach for the segmentation of three-dimensional fields of probability density functions. This presents a wide range of applications in medical images proc...
Christophe Lenglet, Mikaël Rousson, Rachid De...
ACL
2004
13 years 9 months ago
Annealing Techniques For Unsupervised Statistical Language Learning
Exploiting unannotated natural language data is hard largely because unsupervised parameter estimation is hard. We describe deterministic annealing (Rose et al., 1990) as an appea...
Noah A. Smith, Jason Eisner