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ICMLA
2007
13 years 7 months ago
Maximum Likelihood Quantization of Genomic Features Using Dynamic Programming
Dynamic programming is introduced to quantize a continuous random variable into a discrete random variable. Quantization is often useful before statistical analysis or reconstruct...
Mingzhou (Joe) Song, Robert M. Haralick, Sté...
ICML
2003
IEEE
14 years 6 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
PAMI
2007
97views more  PAMI 2007»
13 years 5 months ago
Statistical Performance Evaluation of Biometric Authentication Systems Using Random Effects Models
As biometric authentication systems become more prevalent, it is becoming increasingly important to evaluate their performance. The current paper introduces a novel statistical me...
Sinjini Mitra, Marios Savvides, Anthony Brockwell
ICIP
2006
IEEE
14 years 7 months ago
Laplace Random Vectors, Gaussian Noise, and the Generalized Incomplete Gamma Function
Wavelet domain statistical modeling of images has focused on modeling the peaked heavy-tailed behavior of the marginal distribution and on modeling the dependencies between coeffi...
Ivan W. Selesnick
EMNLP
2008
13 years 7 months ago
Lattice-based Minimum Error Rate Training for Statistical Machine Translation
Minimum Error Rate Training (MERT) is an effective means to estimate the feature function weights of a linear model such that an automated evaluation criterion for measuring syste...
Wolfgang Macherey, Franz Josef Och, Ignacio Thayer...