ICPR
2010
IEEE
13 years 10 months ago
2010
IEEE
In this paper we present a new architecture for face recognition with a single reference image, which completely separates the training process from the recognition process. In th...
TCS
2010
13 years 10 months ago
2010
We present a new approach for an average-case analysis of algorithms and data structures that supports a non-uniform distribution of the inputs and is based on the maximum likelih...
PR
2002
14 years 2 days ago
2002
The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ' function, involving two hyper...
INFORMATICALT
2000
14 years 7 days ago
2000
Abstract. This paper deals with maximum likelihood and least square segmentation of autoregressive random sequences with abruptly changing parameters. Conditional distribution of t...
BMCBI
2005
14 years 10 days ago
2005
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
SIGPRO
2008
14 years 10 days ago
2008
The LMS algorithm is one of the most popular learning algorithms for identifying an unknown system. Many variants of the algorithm have been developed based on different problem f...
ML
2008
ACM
14 years 12 days ago
2008
ACM
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
JACM
2006
14 years 12 days ago
2006
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...
IJCBDD
2008
14 years 13 days ago
2008
: Phylogenetic search is a key tool used in a variety of biological research endeavors. However, this search problem is known to be computationally difficult, due to the astronomic...
IJAR
2008
14 years 13 days ago
2008
We present Bayesian updating of an imprecise probability measure, represented by a class of precise multidimensional probability measures. Choice and analysis of our class are mot...