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C⁴: Exploring Multiple Solutions in Graphical Models by Cluster Sampling

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2011年第9期33卷 1713-1727页

作者： Porway, Jake Zhu, Song-Chun New York Times Co R&D Div New York NY USA Univ Calif Los Angeles Dept Stat Los Angeles CA 90024 USA Univ Calif Los Angeles Dept Comp Sci Los Angeles CA 90024 USA

This paper presents a novel Markov Chain Monte Carlo (MCMC) inference algorithm called C-4-Clustering with Cooperative and Competitive Constraints-for computing multiple solutions from posterior probabilities defined on graphical models, including Markov random fields (MRF), conditional random fields (CRF), and hierarchical models. The graphs may have both positive and negative edges for cooperative and competitive constraints. C-4 is a probabilistic clustering algorithm in the spirit of Swendsen-Wang [34]. By turning the positive edges on/off probabilistically, C-4 partitions the graph into a number of connected components (ccps) and each ccp is a coupled subsolution with nodes connected by positive edges. Then, by turning the negative edges on/off probabilistically, C-4 obtains composite ccps (called cccps) with competing ccps connected by negative edges. At each step, C-4 flips the labels of all nodes in a cccp so that nodes in each ccp keep the same label while different ccps are assigned different labels to observe both positive and negative constraints. Thus, the algorithm can jump between multiple competing solutions (or modes of the posterior probability) in a single or a few steps. It computes multiple distinct solutions to preserve the intrinsic ambiguities and avoids premature commitments to a single solution that may not be valid given later context. C-4 achieves a mixing rate faster than existing MCMC methods, such as various Gibbs samplers [15], [26] and Swendsen-Wang cuts [2], [34]. It is also more "dynamic" than common optimization methods such as ICM [3], LBP [21], [37], and graph cuts [4], [20]. We demonstrate the C4 algorithm in line drawing interpretation, scene labeling, and object recognition.

关键词： Markov random fields computer vision graph labeling probabilistic algorithms constraint satisfaction Monte Carlo

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Natural Character Posing from a Large Motion Database

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IEEE COMPUTER GRAPHICS AND APPLICATIONS 2011年第3期31卷 69-77页

作者： Wu, Xiaomao Tournier, Maxime Reveret, Lionel Crytek R&D Dept Frankfurt Studio Frankfurt Germany

An interactive inverse kinematics approach robustly generates natural poses in a large human-reachable space. It employs adaptive kd clustering to select a representative frame set from a large motion database and emp... 详细信息

关键词： 3D graphics and realism Acceleration Animation Approximation algorithms artificial intelligence Carbon capture and storage computer graphics Databases Educational institutions graphics and multimedia Kinematics kinematics and dynamics Packaging probabilistic algorithms robotics Robustness

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On the Distribution of the Number of Cycles in the Breakpoint Graph of a Random Signed Permutation

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2011年第5期8卷 1411-1416页

作者： Grusea, Simona Univ Aix Marseille 1 LATP UMR CNRS 6632 Equipe EBM F-31077 Toulouse 4 France Univ Toulouse Dept GMM Inst Math Toulouse INSA Toulouse F-31077 Toulouse 4 France

We use the finite Markov chain embedding technique to obtain the distribution of the number of cycles in the breakpoint graph of a random uniform signed permutation. This further gives a very good approximation of the... 详细信息

关键词： Markov processes probabilistic algorithms distribution functions biology and genetics

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On the use of Monte Carlo simulation, cache and splitting techniques to improve the Clarke and Wright savings heuristics

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2011年第6期62卷 1085-1097页

作者： Juan, A. A. Faulin, J. Jorba, J. Riera, D. Masip, D. Barrios, B. Univ Publ Navarra Pamplona 31006 Spain Open Univ Catalonia Barcelona Spain

This paper presents the SR-GCWS-CS probabilistic algorithm that combines Monte Carlo simulation with splitting techniques and the Clarke and Wright savings heuristic to find competitive quasi-optimal solutions to the Capacitated Vehicle Routing Problem (CVRP) in reasonable response times. The algorithm, which does not require complex fine-tuning processes, can be used as an alternative to other metaheuristics such as Simulated Annealing, Tabu Search, Genetic algorithms, Ant Colony Optimization or GRASP, which might be more difficult to implement and which might require non-trivial fine-tuning processes when solving CVRP instances. As discussed in the paper, the probabilistic approach presented here aims to provide a relatively simple and yet flexible algorithm which benefits from: (a) the use of the geometric distribution to guide the random search process, and (b) efficient cache and splitting techniques that contribute to significantly reduce computational times. The algorithm is validated through a set of CVRP standard benchmarks and competitive results are obtained in all tested cases. Future work regarding the use of parallel programming to efficiently solve large-scale CVRP instances is discussed. Finally, it is important to notice that some of the principles of the approach presented here might serve as a base to develop similar algorithms for other routing and scheduling combinatorial problems. Journal of the Operational Research Society (2011) 62, 1085-1097. doi: 10.1057/jors.2010.29 Published online 19 May 2010

关键词： simulation heuristics probabilistic algorithms vehicle routing road transport

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probabilistic matching of planar regions

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COMPUTATIONAL GEOMETRY-THEORY AND APPLICATIONS 2010年第2期43卷 99-114页

作者： Alt, Helmut Scharf, Ludmila Schymura, Daria Free Univ Berlin Inst Informat D-1000 Berlin Germany

We analyze a probabilistic algorithm for matching shapes modeled by planar regions under translations and rigid motions (rotation and translation). Given shapes A and B, the algorithm computes a transformation t such that with high probability the area of overlap of t(A) and B is close to maximal. In the case of polygons, we give a time bound that does not depend significantly on the number of vertices, but on perimeter and area of the shapes and, in the case of rigid motions, also on the diameter. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Computational geometry Shape matching probabilistic algorithms Approximation algorithms

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Model Fitting with Sufficient Random Sample Coverage

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INTERNATIONAL JOURNAL OF COMPUTER VISION 2010年第1期89卷 120-128页

作者： Scherer-Negenborn, Norbert Schaefer, Rolf FGAN FOM Ettlingen Germany

It has been observed previously that the number of iterations required to derive good model parameter values used by RANSAC-like model estimators is too optimistic. We present the derivation of an analytical formula that allows the calculation of the sufficient limit of iterations needed to obtain good parameter values with the prescribed probability for any number of model parameters. It explains the values that had been found experimentally for certain numbers of model parameters by others very well. Furthermore, the improvement that our approach of SUfficient Random SAmple Coverage (SURSAC) offers, in comparison to the original RANSAC algorithm as well as to its adaptive modification by Hartley and Zisserman, is demonstrated with synthetic data for the case of a non-linear model function over a wide range of outlier fractions and different ratios of inlier and outlier densities.

关键词： Model fitting probabilistic algorithms RANSAC Robust regression

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probabilistic matching of planar regions

Probabilistic matching of planar regions

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作者： Alt, Helmut Scharf, Ludmila Schymura, Daria Institut für Informatik Freie Universität Berlin Berlin Germany

关键词： Approximation algorithms Computational geometry probabilistic algorithms Shape matching

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On the energy balance problem in distributed sensor networks

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COMPUTER SCIENCE REVIEW 2010年第2期4卷 65-79页

作者： Nikoletseas, Sotiris Univ Patras Comp Technol Inst Patras Greece

We investigate the problem of how to achieve energy balanced data propagation in distributed wireless sensor networks. The energy balance property guarantees that the average per sensor energy dissipation is the same for all sensors in the network, throughout the execution of the data propagation protocol. This property is crucial for prolonging the network lifetime, by avoiding early energy depletion of sensors. We survey representative solutions from the state of the art. We first present a basic algorithm that in each step probabilistically decides whether to propagate data one-hop towards the final destination (the sink), or to send it directly to the sink. This randomized choice trades-off the (cheap, but slow) one-hop transmissions with the direct transmissions to the sink, which are more expensive but bypass the bottleneck region around the sink and propagate data fast. By a detailed analysis using properties of stochastic processes and recurrence relations we precisely estimate (even in closed form) the probability for each propagation option necessary for energy balance. The fact (shown by our analysis) that direct (expensive) transmissions to the sink are needed only rarely, shows that our protocol, besides energy balanced, is also energy efficient. We then enhance this basic result by surveying some recent findings including a generalized algorithm and demonstrating the optimality of this two-way probabilistic data propagation, as well as providing formal proofs of the energy optimality of the energy balance property. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Distributed computing Sensor networks Energy efficiency Routing probabilistic algorithms

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CED²: Communication Efficient Disjointness Decision

CED<SUP>2</SUP>: Communication Efficient Disjointness Decisi...

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6th International Conference on Security and Privacy in Communication Networks (SecureComm 2010)

作者： Marconi, Luciana Conti, Mauro Di Pietro, Roberto Univ Roma La Sapienza Dept Comp Sci I-00198 Rome Italy Vrije Univ Amsterdam Dept Comp Sci NL-1081 HV Amsterdam Netherlands Univ Rome Tre Dept Math I-00146 Rome Italy

ISBN: (纸本)9783642161605

Enforcing security often requires the two legitimate parties of a communication to determine whether they share a secret, without disclosing information (e.g. the shared secret itself, or just the existence of such a secret) to third parties-or even to the other party, if it is not the legitimate party but an adversary pretending to impersonate the legitimate one. In this paper, we propose CED2 (Communication Efficient Disjointness Decision), a probabilistic and distributed protocol that allows two parties-each one having a finite set of elements-to decide about the disjointness of their sets. CED2 is particularly suitable for devices having constraints on energy, communication, storage, and bandwidth. Examples of these devices are satellite phones, or nodes of wireless sensor networks. We show that CED2 significantly improves the communication cost compared to the state of the art, while providing the same degree of privacy and security. Analysis and simulations support the findings.

关键词： sets disjointness test communication complexity privacy security probabilistic algorithms

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Brief Announcement: Asynchronous Bounded Expected Delay Networks

Brief Announcement: Asynchronous Bounded Expected Delay Netw...

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29th ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing

作者： Bakhshi, Rena Endrullis, Jorg Fokkink, Wan Pang, Jun Vrije Univ Amsterdam Dept Comp Sci NL-1081 HV Amsterdam Netherlands

ISBN: (纸本)9781605588889

We propose a natural generalisation of asynchronous bounded delay (ABD) network models. The commonly used ABD models assume a known bound on message delay. This assumption is often too strict for real-life applications. To this end we introduce a novel probabilistic network model, called asynchronous bounded expected delay (ABE), which requires a known bound on the expected message delay. While the conditions of ABD networks restrict the set of possible executions, in ABE networks all asynchronous executions are possible, but executions with extremely long delays are less probable. The ABE model captures asynchrony that occurs in sensor networks and ad-hoc networks.

关键词： ABD networks probabilistic algorithms anonymous networks

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