Results 1  10
of
5,679
Graphical models, exponential families, and variational inference
, 2008
"... The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building largescale multivariate statistical models. Graphical models have become a focus of research in many statistical, computational and mathematical fiel ..."
Abstract

Cited by 819 (28 self)
 Add to MetaCart
of probability distributions — are best studied in the general setting. Working with exponential family representations, and exploiting the conjugate duality between the cumulant function and the entropy for exponential families, we develop general variational representations of the problems of computing
Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences
 ACOUSTICS, SPEECH AND SIGNAL PROCESSING, IEEE TRANSACTIONS ON
, 1980
"... Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllableoriented continuous speech recognition system. The vocabulary included many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain phonetically ..."
Abstract

Cited by 1120 (2 self)
 Add to MetaCart
Several parametric representations of the acoustic signal were compared as to word recognition performance in a syllableoriented continuous speech recognition system. The vocabulary included many phonetically similar monosyllabic words, therefore the emphasis was on ability to retain
VARIATIONAL REPRESENTATIONS OF VARADHAN FUNCTIONALS
, 2000
"... Abstract. Motivated by the theory of large deviations, we introduce a class of nonnegative nonlinear functionals that have a variational “rate function” representation. 1. ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
Abstract. Motivated by the theory of large deviations, we introduce a class of nonnegative nonlinear functionals that have a variational “rate function” representation. 1.
KernelBased Object Tracking
, 2003
"... A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatiallysmooth similarity fu ..."
Abstract

Cited by 900 (4 self)
 Add to MetaCart
A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatiallysmooth similarity
Latent dirichlet allocation
 Journal of Machine Learning Research
, 2003
"... We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a threelevel hierarchical Bayesian model, in which each item of a collection is modeled as a finite mixture over an underlying set of topics. Each topic is, ..."
Abstract

Cited by 4365 (92 self)
 Add to MetaCart
, in turn, modeled as an infinite mixture over an underlying set of topic probabilities. In the context of text modeling, the topic probabilities provide an explicit representation of a document. We present efficient approximate inference techniques based on variational methods and an EM algorithm
Local features and kernels for classification of texture and object categories: a comprehensive study
 International Journal of Computer Vision
, 2007
"... Recently, methods based on local image features have shown promise for texture and object recognition tasks. This paper presents a largescale evaluation of an approach that represents images as distributions (signatures or histograms) of features extracted from a sparse set of keypoint locations an ..."
Abstract

Cited by 653 (34 self)
 Add to MetaCart
the influence of background correlations on recognition performance via extensive tests on the PASCAL database, for which groundtruth object localization information is available. Our experiments demonstrate that image representations based on distributions of local features are surprisingly effective
A Variational Representation for Certain Functionals of Brownian Motion
, 1997
"... In this paper we show that the variational representation \Gamma log Ee \Gammaf (W ) = inf v E ae 1 2 Z 1 0 kv s k 2 ds + f ` W + Z \Delta 0 v s ds 'oe holds, where W is a standard d\Gammadimensional Brownian motion, f is any bounded measurable function that maps C([0; 1] : IR ..."
Abstract

Cited by 47 (12 self)
 Add to MetaCart
In this paper we show that the variational representation \Gamma log Ee \Gammaf (W ) = inf v E ae 1 2 Z 1 0 kv s k 2 ds + f ` W + Z \Delta 0 v s ds 'oe holds, where W is a standard d\Gammadimensional Brownian motion, f is any bounded measurable function that maps C([0; 1] : IR
Variational Representations for Continuous Time Processes
, 2009
"... A variational formula for positive functionals of a Poisson random measure and Brownian motion is proved. The formula is based on the relative entropy representation for exponential integrals, and can be used to prove large deviation type estimates. A general large deviation result is proved, and il ..."
Abstract

Cited by 11 (5 self)
 Add to MetaCart
A variational formula for positive functionals of a Poisson random measure and Brownian motion is proved. The formula is based on the relative entropy representation for exponential integrals, and can be used to prove large deviation type estimates. A general large deviation result is proved
2006a), ‘Ambiguity aversion, robustness, and the variational representation of preferences
 Econometrica
"... We characterize, in the Anscombe–Aumann framework, the preferences for which there are a utility function u on outcomes and an ambiguity index c on the set of probabilities on the states of the world such that, for all acts f and g, f � g ⇔ min ..."
Abstract

Cited by 144 (19 self)
 Add to MetaCart
We characterize, in the Anscombe–Aumann framework, the preferences for which there are a utility function u on outcomes and an ambiguity index c on the set of probabilities on the states of the world such that, for all acts f and g, f � g ⇔ min
Variational Representations for Continuous Time Processes
, 2010
"... A variational formula for positive functionals of a Poisson random measure and Brownian motion is proved. The formula is based on the relative entropy representation for exponential integrals, and can be used to prove large deviation type estimates. A general large deviation result is proved, and il ..."
Abstract
 Add to MetaCart
A variational formula for positive functionals of a Poisson random measure and Brownian motion is proved. The formula is based on the relative entropy representation for exponential integrals, and can be used to prove large deviation type estimates. A general large deviation result is proved
Results 1  10
of
5,679