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125,589
Reconstruction/Nonreconstruction Thresholds for Colourings of General GaltonWatson Trees.
"... The broadcasting models on trees arise in many contexts such as discrete mathematics, biology, information theory, statistical physics and computer science. Here we consider the kcolouring model. A basic question here is whether the root’s assignment affects the distribution of the colourings at ..."
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= (1 − )d / ln d we have reconstruction. In this work, we consider the case where the underlying tree is a random one. In particular, our focus is on the wellknown GaltonWatson trees. This model arises naturally in many contexts, e.g. the theory of spinglasses and its applications on random
Growth of GaltonWatson trees: immigration and lifetimes
, 2010
"... We study certain consistent families (Fλ)λ≥0 of GaltonWatson forests with lifetimes as edge lengths and/or immigrants as progenitors of the trees in Fλ. Specifically, consistency here refers to the property that for each µ ≤ λ, the forest Fµ has the same distribution as the subforest of Fλ spanned ..."
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Cited by 3 (0 self)
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We study certain consistent families (Fλ)λ≥0 of GaltonWatson forests with lifetimes as edge lengths and/or immigrants as progenitors of the trees in Fλ. Specifically, consistency here refers to the property that for each µ ≤ λ, the forest Fµ has the same distribution as the subforest of Fλ spanned
regime of Markov chains on GaltonWatson trees
, 2009
"... symmetric entropy bound on the nonreconstruction ..."
A survey of generalpurpose computation on graphics hardware
, 2007
"... The rapid increase in the performance of graphics hardware, coupled with recent improvements in its programmability, have made graphics hardware acompelling platform for computationally demanding tasks in awide variety of application domains. In this report, we describe, summarize, and analyze the l ..."
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Cited by 545 (18 self)
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the latest research in mapping generalpurpose computation to graphics hardware. We begin with the technical motivations that underlie generalpurpose computation on graphics processors (GPGPU) and describe the hardware and software developments that have led to the recent interest in this field. We then aim
Mining Frequent Patterns without Candidate Generation: A FrequentPattern Tree Approach
 DATA MINING AND KNOWLEDGE DISCOVERY
, 2004
"... Mining frequent patterns in transaction databases, timeseries databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriorilike candidate set generationandtest approach. However, candidate set generation is still co ..."
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Cited by 1700 (64 self)
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based mining method, FPgrowth, for mining the complete set of frequent patterns by pattern fragment growth.
Efficiency of mining is achieved with three techniques: (1) a large database is compressed into a condensed,
smaller data structure, FPtree which avoids costly, repeated database scans, (2) our
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
, 2003
"... The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements. The ..."
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Cited by 2109 (30 self)
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The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements
Bayesian Network Classifiers
, 1997
"... Recent work in supervised learning has shown that a surprisingly simple Bayesian classifier with strong assumptions of independence among features, called naive Bayes, is competitive with stateoftheart classifiers such as C4.5. This fact raises the question of whether a classifier with less restr ..."
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Cited by 788 (23 self)
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restrictive assumptions can perform even better. In this paper we evaluate approaches for inducing classifiers from data, based on the theory of learning Bayesian networks. These networks are factored representations of probability distributions that generalize the naive Bayesian classifier and explicitly
A Survey of Computer VisionBased Human Motion Capture
 Computer Vision and Image Understanding
, 2001
"... A comprehensive survey of computer visionbased human motion capture literature from the past two decades is presented. The focus is on a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition. Each ..."
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Cited by 508 (14 self)
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A comprehensive survey of computer visionbased human motion capture literature from the past two decades is presented. The focus is on a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition. Each
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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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
Results 1  10
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125,589