One way to approximate inference in richly-connected graphical models is to apply the sum-product algorithm (a.k.a. probability propagation algorithm), while ignoring the fact that the graph has cycles. The sum-produc...
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ISBN:
(纸本)0262122413
One way to approximate inference in richly-connected graphical models is to apply the sum-product algorithm (a.k.a. probability propagation algorithm), while ignoring the fact that the graph has cycles. The sum-product algorithm can be directly applied in Gaussian networks and in graphs for coding, but for many conditional probability functions - including the sigmoid function - direct application of the sum-product algorithm is not possible. We introduce "accumulator networks" that have low local complexity (but exponential global complexity) so the sum-product algorithm can be directly applied. In an accumulator network, the probability of a child given its parents is computed by accumulating the inputs from the parents in a Markov chain or more generally a tree. After giving expressions for inference and learning in accumulator networks, we give results on the "bars problem" and on the problem of extracting translated, overlapping faces from an image.
Let G1 = (P1, E1) and G2 = (P2, E2) with P1 ∩ P2 = ∅ be two t-spanners (t > 1) in the plane. One interesting question is that how one can merge these two t-spanners to make a t-spanner on P1 ∪ P2 by only adding s...
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It is easier to understand an algorithm when it can be seen in interactive mode. The current study implemented four algorithms to construct geometric spanners;the path-greedy, gap-greedy, Θ-graph and Yao-graph algori...
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作者:
Loulergue, F.Lab. of Algorithms
Complexity/Logic University of Paris 12 61 ave. du General de Gaulle F-94010 Créteil Cedex France
The BSλp-calculus is a calculus of functional bulk synchronous parallel (BSP) programs. It is the basis for the design of a bulk synchronous parallel ML language. For data-parallel languages, there are two points of ...
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The BSλp-calculus is a calculus of functional bulk synchronous parallel (BSP) programs. It is the basis for the design of a bulk synchronous parallel ML language. For data-parallel languages, there are two points of view: the programming model where a program is seen as a sequence of operations on parallel vectors, and the execution model where the program is a parallel composition of programs run on each processor of the parallel machine. BSP algorithms are defined by data-parallel algorithms with explicit (physical) processes in order to allow their parallel execution time to be estimated. We present here a distributed evaluation minimally synchronous for BSP execution (which corresponds to the execution model). This distributed evaluation is correct w.r.t. the call-by-value strategy of the BSλp-calculus (which corresponds to the programming model).
We describe the use of object oriented techniques for the specification, architecting, and design of an enterprise monitoring application. Monitoring applications provide situational awareness and monitor aspects of a...
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ISBN:
(纸本)193241519X
We describe the use of object oriented techniques for the specification, architecting, and design of an enterprise monitoring application. Monitoring applications provide situational awareness and monitor aspects of an enterprise's activities. Drawing from a wide variety of static and dynamic data sources, they typically allow a user to specify items of interest, and drill down to obtain real-time or near-real time information on such items. Our paper describes the use of standard UML for modeling and the issues in architecting and designing our J2EE framework based application.
In this work we investigate further the relationship between Petri nets and Spiking Neural P (SNP) systems: we consider SNP systems that have source (no incoming synapse) and sink (no outgoing synapse) neurons, and th...
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An important class of problems can be cast as inference in noisy-OR Bayesian networks, where the binary state of each variable is a logical OR of noisy versions of the states of the variable's parents. For example...
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ISBN:
(纸本)0262122413
An important class of problems can be cast as inference in noisy-OR Bayesian networks, where the binary state of each variable is a logical OR of noisy versions of the states of the variable's parents. For example, in medical diagnosis, the presence of a symptom can be expressed as a noisy-OR of the diseases that may cause the symptom - on some occasions, a disease may fail to activate the symptom. Inference in richly-connected noisy-OR networks is intractable, but approximate methods (e.g., variational techniques) are showing increasing promise as practical solutions. One problem with most approximations is that they tend to concentrate on a relatively small number of modes in the true posterior, ignoring other plausible configurations of the hidden variables. We introduce a new sequential variational method for bipartite noisy-OR networks, that favors including all modes of the true posterior and models the posterior distribution as a tree. We compare this method with other approximations using an ensemble of networks with network statistics that are comparable to the QMR-DT medical diagnostic network.
We introduce a low-cost and compact spectral imaging camera design based on unmodified consumer cameras and a custom camera objective. The device can be used in a high-resolution configuration that measures the spectr...
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We present a novel rendering algorithm that analyses the ray profiles along the line of sight. The profiles are subdivided according to encountered peaks and valleys at so called transition points. The sensitivity of ...
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ISBN:
(纸本)1568813376
We present a novel rendering algorithm that analyses the ray profiles along the line of sight. The profiles are subdivided according to encountered peaks and valleys at so called transition points. The sensitivity of these transition points is calibrated via two thresholds. The slope threshold is based on the magnitude of a peak following a valley, while the peeling threshold measures the depth of the transition point relative to the neighboring rays. This technique separates the dataset into a number of feature layers. The user can scroll through the layers inspecting various features from the current view position. While our technique has been inspired by opacity peeling approach, we demonstrate that we can reveal detectable features even in the third and forth layers for both CT and MRI datasets.
Building facade classification by architectural styles allows categorization of large databases of building images into semantic categories belonging to certain historic periods, regions and cultural influences. Image...
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