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» Selectivity Estimation using Probabilistic Models
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ICML
2005
IEEE
16 years 5 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
AMC
2006
79views more  AMC 2006»
15 years 5 months ago
VC-dimension and structural risk minimization for the analysis of nonlinear ecological models
The problem of distinguishing density-independent (DI) from density-dependent (DD) demographic time series is important for understanding the mechanisms that regulate populations ...
Giorgio Corani, Marino Gatto
FGR
2011
IEEE
198views Biometrics» more  FGR 2011»
14 years 8 months ago
The optimal camera arrangement by a performance model for gait recognition
— Recently, many gait recognition algorithms are proposed, and the optimal camera arrangement is necessary to maximize the performance. In this paper, we propose the optimal came...
Naoki Akae, Yasushi Makihara, Yasushi Yagi
AUTOMATICA
2008
88views more  AUTOMATICA 2008»
15 years 5 months ago
Parameter ranking by orthogonalization - Applied to nonlinear mechanistic models
The paper addresses methods for parameter sensitivity analysis in a large, nonlinear, mechanistic model which is to be run in an online estimation scheme. The parameter sensitivit...
Berit Floor Lund, Bjarne A. Foss
CSL
2007
Springer
15 years 4 months ago
Discriminative n-gram language modeling
This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...
Brian Roark, Murat Saraclar, Michael Collins