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983
A New Class of Upper Bounds on the Log Partition Function
 In Uncertainty in Artificial Intelligence
, 2002
"... Bounds on the log partition function are important in a variety of contexts, including approximate inference, model fitting, decision theory, and large deviations analysis [11, 5, 4]. We introduce a new class of upper bounds on the log partition function, based on convex combinations of distribution ..."
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Cited by 225 (32 self)
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of distributions in the exponential domain, that is applicable to an arbitrary undirected graphical model. In the special case of convex combinations of treestructured distributions, we obtain a family of variational problems, similar to the Bethe free energy, but distinguished by the following desirable
Decision Procedures For Inductive Boolean . . .
 THEORETICAL COMPUTER SCIENCE
, 2003
"... We show how alternating automata provide decision procedures for theequalVofinductivel de#nedBoolfW functions and presentappltfqqVqW to reasoning about parameterizedfamilet of circuits. We use alWzzzEf7q word automata toformalEf familE oflf##WJq structured circuits and alfzzzIPf7 tree automata tofo ..."
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toformal#f famil# of tree structured circuits. We providecomplfzJW bounds for deciding theequalE of function (or circuit) familt) and show how our decision procedures can beimpl##f7qI using BDDs. In comparison to previous work, our approach issimpl#f has bettercomplWJ bounds, and, in the case of treestructured
Deciding welldefinedness of firstorder, objectcreating operations over treestructured data. http://alpha
"... The welldefinedness problem for a database query language consists of checking, given an expression and an input type, whether the semantics of the expression is defined for all inputs adhering to the input type. In this paper we study the welldefinedness problem for a family of firstorder, obje ..."
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Cited by 1 (1 self)
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order, objectcreating query languages which are evaluated in a treestructured, listbased data model. We identify properties of base operations which can make the problem undecidable and give restrictions which are sufficient to ensure decidability. As a direct result, we obtain a large fragment of XQuery
Treestructure expectation propagation for decoding LDPC codes over binary erasure channels
 in IEEE International Symposium on Information Theory Proceedings (ISIT
, 2010
"... Abstract—Expectation Propagation is a generalization to Belief Propagation (BP) in two ways. First, it can be used with any exponential family distribution over the clicks in the graph. Second, it can impose additional constraints on the marginal distributions. We use this second property to impose ..."
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Cited by 5 (4 self)
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Abstract—Expectation Propagation is a generalization to Belief Propagation (BP) in two ways. First, it can be used with any exponential family distribution over the clicks in the graph. Second, it can impose additional constraints on the marginal distributions. We use this second property to impose
Stochastic Dynamic Programming with Factored Representations
, 1997
"... Markov decision processes(MDPs) have proven to be popular models for decisiontheoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, statebased specifications and computations. To alleviate the combinatorial problems associated with such methods, we prop ..."
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Cited by 189 (10 self)
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pose new representational and computational techniques for MDPs that exploit certain types of problem structure. We use dynamic Bayesian networks (with decision trees representing the local families of conditional probability distributions) to represent stochastic actions in an MDP, together with a
Mismatch string kernels for discriminative protein classification
 Bioinformatics
, 2004
"... Motivation: Classification of proteins sequences into functional and structural families based on sequence homology is a central problem in computational biology. Discriminative supervised machine learning approaches provide good performance, but simplicity and computational efficiency of training a ..."
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Cited by 193 (9 self)
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Motivation: Classification of proteins sequences into functional and structural families based on sequence homology is a central problem in computational biology. Discriminative supervised machine learning approaches provide good performance, but simplicity and computational efficiency of training
Squarified Treemaps
 In Proceedings of the Joint Eurographics and IEEE TCVG Symposium on Visualization
, 1999
"... . An extension to the treemap method for the visualization of hierarchical information, such as directory structures and organization structures, is presented. The standard treemap method often gives thin, elongated rectangles. As a result, rectangles are difficult to compare and to select. A new ..."
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Cited by 172 (2 self)
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, organization structures, family trees, catalogues, computer programs, and so on. Small hierarchical structures are effective to locate information, but the content and organization of large structures is harder to grasp. We present a new visualization method for large hierarchical structures: Squarified
Detecting Parallelism in C Programs with Recursive Data Structures
 IEEE Transactions on Parallel and Distributed Systems
, 1998
"... In this paper we present techniques to detect three common patterns of parallelism in C programs that use recursive data structures. These patterns include, function calls that access disjoint subpieces of treelike data structures, pointerchasing loops that traverse listlike data structures, and ..."
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Cited by 168 (13 self)
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In this paper we present techniques to detect three common patterns of parallelism in C programs that use recursive data structures. These patterns include, function calls that access disjoint subpieces of treelike data structures, pointerchasing loops that traverse listlike data structures
Differential Algebra Structures on Families of Trees
, 2004
"... It is known that the vector space spanned by labeled rooted trees forms a Hopf algebra. Let k be a field and let R be a commutative kalgebra. Let H denote the Hopf algebra of rooted trees labeled using derivations D ∈ Der(R). In this paper, we introduce a construction which gives R a Hmodule algeb ..."
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Cited by 2 (0 self)
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It is known that the vector space spanned by labeled rooted trees forms a Hopf algebra. Let k be a field and let R be a commutative kalgebra. Let H denote the Hopf algebra of rooted trees labeled using derivations D ∈ Der(R). In this paper, we introduce a construction which gives R a H
A structured family of clustering and tree construction methods
 ADVANCES IN APPLIED MATHEMATICS
, 2001
"... A cluster A is an Apresjan cluster if every pair of objects within A is more similar than either is to any object outside A. The criterion is intuitive, compelling, but often too restrictive for applications in classification. We therefore explore extensions of Apresjan clustering to a family of rel ..."
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Cited by 14 (5 self)
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of related hierarchical clustering methods. The extensions are shown to be closely connected with the wellknown single and average linkage tree constructions. A dual family of methods for classification by splits is also presented. Splits are partitions of the set of objects into two disjoint blocks
Results 11  20
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983