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ICDM
2006
IEEE
183views Data Mining» more  ICDM 2006»
16 years 6 days ago
Accelerating Newton Optimization for Log-Linear Models through Feature Redundancy
— Log-linear models are widely used for labeling feature vectors and graphical models, typically to estimate robust conditional distributions in presence of a large number of pot...
Arpit Mathur, Soumen Chakrabarti
AIPR
2005
IEEE
15 years 11 months ago
Face Recognition Using Multispectral Random Field Texture Models, Color Content, and Biometric Features
Most of the available research on face recognition has been performed using gray scale imagery. This paper presents a novel two-pass face recognition system that uses a Multispect...
Orlando J. Hernandez, Mitchell S. Kleiman
157
Voted
SOCO
2010
Springer
15 years 4 months ago
Managing Variability in Workflow with Feature Model Composition Operators
Abstract. In grid-based scientific applications, building a workflow essentially involves composing parameterized services describing families of services and then configuring the ...
Mathieu Acher, Philippe Collet, Philippe Lahire, R...
173
Voted
INTERSPEECH
2010
15 years 29 days ago
Feature versus model based noise robustness
Over the years, the focus in noise robust speech recognition has shifted from noise robust features to model based techniques such as parallel model combination and uncertainty de...
Kris Demuynck, Xueru Zhang, Dirk Van Compernolle, ...
208
Voted
TSP
2010
15 years 25 days ago
A multi-resolution hidden Markov model using class-specific features
We address the problem in signal classification applications, such as automatic speech recognition (ASR) systems that employ the hidden Markov model (HMM), that it is necessary to...
Paul M. Baggenstoss