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TASLP
2002
84views more  TASLP 2002»
15 years 3 months ago
Maximum likelihood multiple subspace projections for hidden Markov models
The first stage in many pattern recognition tasks is to generate a good set of features from the observed data. Usually, only a single feature space is used. However, in some compl...
Mark J. F. Gales
ICML
2006
IEEE
16 years 5 months ago
Graph model selection using maximum likelihood
In recent years, there has been a proliferation of theoretical graph models, e.g., preferential attachment and small-world models, motivated by real-world graphs such as the Inter...
Adam Kalai, Ivona Bezáková, Rahul Sa...
PAMI
2010
132views more  PAMI 2010»
15 years 2 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel
JSC
2006
102views more  JSC 2006»
15 years 4 months ago
Counting and locating the solutions of polynomial systems of maximum likelihood equations, I
In statistics, mixture models consisting of several component subpopulations are used widely to model data drawn from heterogeneous sources. In this paper, we consider maximum lik...
Max-Louis G. Buot, Donald St. P. Richards

Publication
204views
15 years 1 months ago
Maximum Likelihood Active Contours Specialized for Mammography Segmentation
We present a region-based active contour approach to segmenting masses in digital mammograms. The algorithm developed in a Maximum Likelihood approach is based on the calculation o...
Peyman Rahmati, A. Ayatollahi