Results 11  20
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6,360
Information consensus for distributed multitarget tracking
 In IEEE Conf. on Computer Vision and Pattern Recognition
, 2013
"... Due to their high faulttolerance, ease of installation and scalability to large networks, distributed algorithms have recently gained immense popularity in the sensor networks community, especially in computer vision. Multitarget tracking in a camera network is one of the fundamental problems in ..."
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Cited by 6 (1 self)
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of naivety, are jointly addressed leading to the development of an informationweighted consensus algorithm, which we term as the Multitarget Information Consensus (MTIC) algorithm. The incorporation of the probabilistic data association mechanism makes the MTIC algorithm very robust to false mea
A scaled conjugate gradient algorithm for fast supervised learning
 NEURAL NETWORKS
, 1993
"... A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural netwo ..."
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Cited by 451 (0 self)
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A supervised learning algorithm (Scaled Conjugate Gradient, SCG) with superlinear convergence rate is introduced. The algorithm is based upon a class of optimization techniques well known in numerical analysis as the Conjugate Gradient Methods. SCG uses second order information from the neural
Simple statistical gradientfollowing algorithms for connectionist reinforcement learning
 Machine Learning
, 1992
"... Abstract. This article presents a general class of associative reinforcement learning algorithms for connectionist networks containing stochastic units. These algorithms, called REINFORCE algorithms, are shown to make weight adjustments in a direction that lies along the gradient of expected reinfor ..."
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Cited by 449 (0 self)
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Abstract. This article presents a general class of associative reinforcement learning algorithms for connectionist networks containing stochastic units. These algorithms, called REINFORCE algorithms, are shown to make weight adjustments in a direction that lies along the gradient of expected
Information Weighted Consensus Filters and their Application in Distributed Camera Networks
"... Abstract—Due to their high faulttolerance and scalability to large networks, consensusbased distributed algorithms have recently gained immense popularity in the sensor networks community. Large scale camera networks are a special case. In a consensusbased state estimation framework, multiple nei ..."
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Cited by 5 (1 self)
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and measurement information. Motivated by this idea, we propose informationweighted consensus algorithms for distributed maximum a posteriori parameter estimation, and their extension to the informationweighted consensus filter (ICF) for state estimation. We compare the performance of the ICF with existing
A majority consensus approach to concurrency control for multiple copy databases
 ACM Transactions on Database Systems
, 1979
"... A “majority consensus ” algorithm which represents a new solution to the update synchronization problem for multiple copy databases is presented. The algorithm embodies distributed control and can function effectively in the presence of communication and database site outages. The correctness of the ..."
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Cited by 376 (0 self)
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A “majority consensus ” algorithm which represents a new solution to the update synchronization problem for multiple copy databases is presented. The algorithm embodies distributed control and can function effectively in the presence of communication and database site outages. The correctness
R: RNA sequence analysis using covariance models. Nucleic Aeids Res
, 1994
"... We describe a general approach to several RNA sequence analysis problems using probabilistic models that flexibly describe the secondary structure and primary sequence consensus of an RNA sequence family. We call these models 'covariance models'. A covariance model of tRNA sequences is an ..."
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Cited by 367 (9 self)
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is an extremely sensitive and discriminative tool for searching for additional tRNAs and tRNArelated sequences in sequence databases. A model can be built automatically from an existing sequence alignment. We also describe an algorithm for learning a model and hence a consensus secondary structure from initially
A scheme for robust distributed sensor fusion based on average consensus
 PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN
, 2005
"... We consider a network of distributed sensors, where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a simple distributed iterative scheme, based on distributed average consensus in the network, to compute the maximumlikelihoo ..."
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Cited by 257 (3 self)
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likelihood estimate of the parameters. This scheme doesn’t involve explicit pointtopoint message passing or routing; instead, it diffuses information across the network by updating each node’s data with a weighted average of its neighbors ’ data (they maintain the same data structure). At each step, every node can
Broadcast gossip algorithms for consensus
 IEEE TRANS. SIGNAL PROCESS
, 2009
"... Motivated by applications to wireless sensor, peertopeer, and ad hoc networks, we study distributed broadcasting algorithms for exchanging information and computing in an arbitrarily connected network of nodes. Specifically, we study a broadcastingbased gossiping algorithm to compute the (possib ..."
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Cited by 93 (7 self)
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the (possibly weighted) average of the initial measurements of the nodes at every node in the network. We show that the broadcast gossip algorithm converges almost surely to a consensus. We prove that the random consensus value is, in expectation, the average of initial node measurements and that it can be made
Convergence in multiagent coordination, consensus, and flocking
 IN PROCEEDINGS OF THE JOINT 44TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE
, 2005
"... We discuss an old distributed algorithm for reaching consensus that has received a fair amount of recent attention. In this algorithm, a number of agents exchange their values asynchronously and form weighted averages with (possibly outdated) values possessed by their neighbors. We overview existing ..."
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Cited by 232 (15 self)
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We discuss an old distributed algorithm for reaching consensus that has received a fair amount of recent attention. In this algorithm, a number of agents exchange their values asynchronously and form weighted averages with (possibly outdated) values possessed by their neighbors. We overview
Quantized consensus
, 2007
"... We study the distributed averaging problem on arbitrary connected graphs, with the additional constraint that the value at each node is an integer. This discretized distributed averaging problem models several problems of interest, such as averaging in a network with finite capacity channels and loa ..."
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Cited by 144 (0 self)
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and load balancing in a processor network. We describe simple randomized distributed algorithms which achieve consensus to the extent that the discrete nature of the problem permits. We give bounds on the convergence time of these algorithms for fully connected networks and linear networks.
Results 11  20
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6,360