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791,814
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 ..."
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Cited by 800 (26 self)
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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
Boosting and Maximum Likelihood for Exponential Models
 In Advances in Neural Information Processing Systems
, 2001
"... Recent research has considered the relationship between boosting and more standard statistical methods, such as logistic regression, concluding that AdaBoost is similar but somehow still very different from statistical methods in that it minimizes a different loss function. In this paper we derive a ..."
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Cited by 97 (6 self)
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an equivalence between AdaBoost and the dual of a convex optimization problem. In this setting, it is seen that the only difference between minimizing the exponential loss used by AdaBoost and maximum likelihood for exponential models is that the latter requires the model to be normalized to form a conditional
Tracking People with Twists and Exponential Maps
, 1998
"... This paper demonstrates a new visual motion estimation technique that is able to recover high degreeoffreedom articulated human body configurations in complex video sequences. We introduce the use of a novel mathematical technique, the product of exponential maps and twist motions, and its integra ..."
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Cited by 443 (5 self)
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This paper demonstrates a new visual motion estimation technique that is able to recover high degreeoffreedom articulated human body configurations in complex video sequences. We introduce the use of a novel mathematical technique, the product of exponential maps and twist motions, and its
Maximum entropy markov models for information extraction and segmentation
, 2000
"... Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many textrelated tasks, such as partofspeech tagging, text segmentation and information extraction. In these cases, the observations are usually modeled as multinomial ..."
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Cited by 554 (18 self)
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, capitalization, formatting, partofspeech), and defines the conditional probability of state sequences given observation sequences. It does this by using the maximum entropy framework to fit a set of exponential models that represent the probability of a state given an observation and the previous state. We
ON EXPONENTIAL MODEL OF POISSON SPACES
"... Abstract. We generalize N.Privault’s interpretation of Poisson space over R as the space of sequences with exponential product measure. The proposed model of Poisson spaces enables to reformulate the recent results in analysis and geometry in Poisson spaces in the classical framework of infinite dim ..."
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Abstract. We generalize N.Privault’s interpretation of Poisson space over R as the space of sequences with exponential product measure. The proposed model of Poisson spaces enables to reformulate the recent results in analysis and geometry in Poisson spaces in the classical framework of infinite
Estimation on Exponential Model with Limited Replacements
"... We consider the estimation of parameter in the exponential model in the case that the number of replacements of failed items is limited. And the desirable number of replacements to give the similar effect as unlimited case in terms of the mean square errors is proposed. ..."
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Cited by 1 (1 self)
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We consider the estimation of parameter in the exponential model in the case that the number of replacements of failed items is limited. And the desirable number of replacements to give the similar effect as unlimited case in terms of the mean square errors is proposed.
An Exponential Model for Infinite Rankings
 Journal of Machine Learning Research
"... This paper presents a statistical model for expressing preferences through rankings, when the number of alternatives (items to rank) is large. A human ranker will then typically rank only the most preferred items, and may not even examine the whole set of items, or know how many they are. Similarly, ..."
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Cited by 4 (0 self)
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this model from data, and demonstrate that it has sufficient statistics, being thus an exponential family model with continuous and discrete parameters. We describe its conjugate prior and other statistical properties. Then, we extend the estimation problem to multimodal data by introducing an Exponential
INFERENCE IN THE MULTIVARIATE EXPONENTIAL MODELS
"... Block (1975) extended bivariate exponential distributions (BVEDs) of Freund (1961) and Proschan and Sullo (1974) to multivariate case and called them as Generalized FreundWeinman's multivariate exponential distributions (MVEDs). In this paper, we obtain MLEs of the parameters and large sample ..."
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Block (1975) extended bivariate exponential distributions (BVEDs) of Freund (1961) and Proschan and Sullo (1974) to multivariate case and called them as Generalized FreundWeinman's multivariate exponential distributions (MVEDs). In this paper, we obtain MLEs of the parameters and large sample
Consensus ranking under the exponential model
 UAI
, 2007
"... We analyze the generalized Mallows model, a popular exponential model over rankings. Estimating the central (or consensus) ranking from data is NPhard. We obtain the following new results: (1) We show that search methods can estimate both the central ranking π0 and the model parameters θ exactly. T ..."
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Cited by 34 (5 self)
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We analyze the generalized Mallows model, a popular exponential model over rankings. Estimating the central (or consensus) ranking from data is NPhard. We obtain the following new results: (1) We show that search methods can estimate both the central ranking π0 and the model parameters θ exactly
Results 1  10
of
791,814