[PDF] Top 20 Memoria Descriptiva Para Licencia de Uso de Agua
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Loopy Belief Propagation: Convergence and Effects of Message Errors
... Figure 8(a) shows the maximum KL-divergence from the correct fixed point resulting in each Monte Carlo trial for a grid with relatively weak potentials (in which loopy BP is analytically guar- anteed to converge). ... See full document
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Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees
... to belief propagation with con- tinuous ...series message-passing (SOSMP), is applicable to general pairwise Markov random fields, and is equipped with various theoretical ...the convergence ... See full document
9
Convergence Analysis of Distributed Inference with Vector-Valued Gaussian Belief Propagation
... of convergence in loopy net- works (Chertkov and Chernyak, 2006; G´ omez et ...2007). Convergence of other forms of loopy BP are analyzed by Ihler et ...Sufficient convergence ... See full document
5
Fast Inference in Phrase Extraction Models with Belief Propagation
... these effects, the recent phrase alignment work of DeNero and Klein (2010) mod- els extraction sets: collections of overlapping phrase pairs that are consistent with an underlying word ... See full document
83
Truncating the Loop Series Expansion for Belief Propagation
... In this work we propose TLSBP, an algorithm to compute generalized loops in a graph which are then used for the approximate computation of the partition sum and the single-node marginals. The proposed algorithm is ... See full document
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Efficient Decoding of Turbo Codes with Nonbinary Belief Propagation
... the other preprocessings, which is explained by the fact that the corresponding Tanner graph has less nonzero clusters. It can be seen that with a good preprocessing function, a turbo code can be efficiently decoded using ... See full document
10
Calibrating Distributed Camera Networks Using Belief Propagation
... We discuss how to obtain the accurate and globally consistent self-calibration of a distributed camera network, in which camera nodes with no centralized processor may be spread over a wide geographical area. We present ... See full document
17
Walk-Sums and Belief Propagation in Gaussian Graphical Models
... and m (n) i→ j = m (n−1) i→j for the other messages. For example, in the fully parallel case all messages are updated at each iteration whereas, in serial versions, only one message is updated at each iteration. ... See full document
10
Approximation Aware Dependency Parsing by Belief Propagation
... using loopy belief propagation through structured ...the errors introduced by this approximation, by following the gradient of the actual loss on training ...for loopy CRFs (Domke, ... See full document
40
Structured Learning for Taxonomy Induction with Belief Propagation
... With the model defined, there are two main in- ference tasks we wish to accomplish: computing expected feature counts and selecting a particular taxonomy tree for a given set of input terms (de- coding). As an initial ... See full document
137
Analogue MIMO detection on the basis of belief propagation
... This message update rule results in optimal inference in graphs without loops, but also can provide excellent results for sparse loopy graphs. The mechanism is best represented in a factor graph [6] such as ... See full document
14
Modeling Political Belief and Its Propagation, with Malaysia as a Driving Context
... We discuss in this paper an agent-based social simulation model that describes the propagation of political belief in Malaysia.. Worldview map is used as the representational scheme for[r] ... See full document
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The equivalence between the convergences of Mann and Ishikawa iteration methods with errors for demicontinuous φ strongly accretive operators in uniformly smooth Banach spaces
... Therefore, T is φ-strongly accretive. Consequently, Theorem 2.1 ensures the equiva- lence of the Mann iteration method with errors and the Ishikawa iteration method with errors for φ-strongly accretive ... See full document
168
Block Belief Propagation for Parameter Learning in Markov Random Fields
... For future work, we plan to use the scalability of BBPL to analyze large-scale networks. Further speedups may be possible. Even though BBPL only needs to run inference on a subnetwork, it still needs to run many ... See full document
70
Robust all source positioning of UAVs based on belief propagation
... the belief propagation process, which is help- ful in improving the positioning performance of all nodes (especially nodes 2 to 5), so the overall performance of case 1 is better than that of case ... See full document
16
Multi-radio network optimisation using Bayesian belief propagation
... To determine the impact of station assignments, the BBN in Fig. 2 is used for the GHz network with the estimated transmit power re- quired for each possible assignment estimated in Fig 4 as discussed in Sec. 3.4. Fig. 6 ... See full document
6
Radiator - efficient message propagation in context-aware systems
... age message propagation ...a message) caused by ...exist message retention on the net- work link so we might as well retain them at the ... See full document
152
Linear Programming Relaxations and Belief Propagation -- An Empirical Study
... Tree-Reweighted Belief Propagation is a promising recent algorithm for solving LP relaxations, but little is known about its running time on large ... See full document
6
Convergence of Gaussian Belief Propagation Under General Pairwise Factorization: Connecting Gaussian MRF with Pairwise Linear Gaussian Model
... the convergence condition of belief variances under synchronous and totally asynchronous schedulings stays the same, ...BP message precision α ∗ stays the same for both synchronous and totally ... See full document
128
On the Convergence of Gaussian Belief Propagation with Nodes of Arbitrary Size
... the convergence behavior of application to the different sets of inputs can be substantial, in the sense that the preconditioned variant converges much faster (Shewchuk, ... See full document
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