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UAI
2008
15 years 8 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
154
Voted
BMCBI
2008
87views more  BMCBI 2008»
15 years 7 months ago
Evaluation of two methods for computational HLA haplotypes inference using a real dataset
Background: HLA haplotype analysis has been used in population genetics and in the investigation of disease-susceptibility locus, due to its high polymorphism. Several methods for...
Bruno F. Bettencourt, Margarida R. Santos, Raquel ...
BC
2006
83views more  BC 2006»
15 years 6 months ago
An Algorithmic Method for Reducing Conductance-based Neuron Models
Although conductance-based neural models provide a realistic depiction of neuronal activity, their complexity often limits effective implementation and analysis. Neuronal model red...
Michael E. Sorensen, Stephen P. DeWeerth
185
Voted
JEI
2006
110views more  JEI 2006»
15 years 6 months ago
Empirical formula for creating error bars for the method of paired comparison
The method of paired comparison based on Thurstone's Case V of his Law of Comparative Judgments is often used as a psychophysical method to derive interval scales of perceptua...
Ethan D. Montag
INFORMATICALT
2007
75views more  INFORMATICALT 2007»
15 years 6 months ago
An Effective Method for Initialization of Lloyd-Max's Algorithm of Optimal Scalar Quantization for Laplacian Source
Abstract. In this paper an exact and complete analysis of the Lloyd–Max’s algorithm and its initialization is carried out. An effective method for initialization of Lloyd–Max...
Zoran Peric, Jelena Nikolic