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66
Subscription Mechanisms for Network Formation
 Journal of Economic Theory
, 2002
"... We analyze a model of network formation where the costs of link formation are publicly known but individual benefits are not known to the social planner. The objective is to design a simple mechanism ensuring efficiency, budget balance and equity. We propose two mechanisms towards this end; the firs ..."
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Cited by 11 (4 self)
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We analyze a model of network formation where the costs of link formation are publicly known but individual benefits are not known to the social planner. The objective is to design a simple mechanism ensuring efficiency, budget balance and equity. We propose two mechanisms towards this end; the first ensures efficiency and budget balance but not equity. The second mechanism corrects the asymmetry in payoffs through a twostage variant of the first mechanism. We also discuss an extension of the basic model to cover the case of directed graphs and give conditions under which the proposed mechanisms are immune to coalitional deviations. We thank Francis Bloch, an associate editor and an anonymous referee for their comments on this paper. A previous version was written when Mutuswami was visiting CORE, Belgium. He thanks them for their support.
Muvis: A contentbased multimedia indexing and retrieval framework
 Proc. of the Seventh International Symposium on Signal Processing and its Applications, ISSPA 2003
, 2003
"... MUVIS is a series of CBIR systems. The first one has been developed in late 90s to support indexing and retrieval in large image databases using visual and semantic features such as color, texture and shape. During recent years. MUVIS has been reformed to become a PCbased framework, which supports ..."
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Cited by 10 (7 self)
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MUVIS is a series of CBIR systems. The first one has been developed in late 90s to support indexing and retrieval in large image databases using visual and semantic features such as color, texture and shape. During recent years. MUVIS has been reformed to become a PCbased framework, which supports indexing, browsing and querying of various multimedia types such as audio. video, audiohideo interlaced and several image formats. MUVIS system allows realtime audio and video capturing, encoding by last generation codecs such as MPEG4. H.263+. MP3 and AAC. It supports several audiohideo file format such as AVI, MP4, MP3 and AAC. Furthermore. MWIS system provides a welldefined interface for third parties to integrate their own feature extraction algorithms into the framework and for this reason it has recently been adopted by COST 21 lquat as COST framework for CBR. In this paper. we describe the general system features with underlying applications and outline the main philosophy. 1.
Online Network Optimization Problems
 In Developments from a
, 1998
"... . We survey results on online versions of the standard network optimization problems, including the minimum spanning tree problem, the minimum Steiner tree problem, the weighted and unweighted matching problems, and the traveling salesman problem. The goal in these problems is to maintain, with mini ..."
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Cited by 10 (1 self)
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. We survey results on online versions of the standard network optimization problems, including the minimum spanning tree problem, the minimum Steiner tree problem, the weighted and unweighted matching problems, and the traveling salesman problem. The goal in these problems is to maintain, with minimal changes, a low cost subgraph of some type in a dynamically changing network. 1 Introduction In the early 1920's Otakar Bor uvka was asked by the Electric Power Company of Western Moravia (EPCWM) to assist in EPCWM's electrification of southern Moravia by solving from a mathematical standpoint the question of how to construct the most economical electric power network [9]. In 1926 Bor uvka initiated the study of network optimization problems, by publishing an efficient algorithm for constructing a minimum spanning tree of a fixed network [9]. Certainly since the 1920's the underlying collection of sites that require electrification in southern Moravia has changed frequently as new sites ...
M.R.: A learning automatabased heuristic algorithm for solving the minimum spanning tree problem in stochastic graphs
, 2010
"... During the last decades, a host of efficient algorithms have been developed for solving the minimum spanning tree problem in deterministic graphs, where the weight associated with the graph edges is assumed to be fixed. Though it is clear that the edge weight varies with time in realistic applicatio ..."
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Cited by 8 (4 self)
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During the last decades, a host of efficient algorithms have been developed for solving the minimum spanning tree problem in deterministic graphs, where the weight associated with the graph edges is assumed to be fixed. Though it is clear that the edge weight varies with time in realistic applications and such an assumption is wrong, finding the minimum spanning tree of a stochastic graph has not received the attention it merits. This is due to the fact that the minimum spanning tree problem becomes incredibly hard to solve when the edge weight is assumed to be a random variable. This becomes more difficult, if we assume that the probability distribution function of the edge weight is unknown. In this paper, we propose a learning automata‐based heuristic algorithm to solve the minimum spanning tree problem in stochastic graphs wherein the probability distribution function of the edge weight is unknown. The proposed algorithm taking advantage of learning automata determines the edges that must be sampled at each stage. As the presented algorithm proceeds, the sampling process is concentrated on the edges that constitute the spanning tree with the minimum expected weight. The proposed learning automata‐based sampling method decreases the number of samples that need to be taken from the graph by reducing the rate of unnecessary samples. Experimental results show the superiority of the proposed algorithm over the well‐known existing methods both in terms of the number of samples and the running time of algorithm.
A new upper bound on the ML decoding error probability of linear binary block codes in AWGN interference
, 2002
"... Performance evaluation of MaximumLikelihood (ML) softdecisiondecoded binary block codes is usually carried out using bounding techniques. Many tight upper bounds on the error probability of binary codes are based on the socalled Gallager's First Bounding Technique (GFBT). The Tangential Sphere B ..."
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Cited by 7 (1 self)
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Performance evaluation of MaximumLikelihood (ML) softdecisiondecoded binary block codes is usually carried out using bounding techniques. Many tight upper bounds on the error probability of binary codes are based on the socalled Gallager's First Bounding Technique (GFBT). The Tangential Sphere Bound (TSB) of Poltyrev which is believed for many years to oer the tightest bound developed for binary block codes is an example. Within the framework of the TSB and GFBT, we apply a new method referred to as the \AddedHyperPlane" (AHP) technique, to the decomposition of the error probability. This results in a bound developed upon the application of two stages of the GFBT with two dierent Gallager regions culminating to a tightened upper bound beyond the TSB. The proposed bound is simple and only requires the spectrum of the binary code.
Parallel MarkerBased Image Segmentation with Watershed Transformation
, 1998
"... The parallel watershed transformation used in grayscale image segmentation is here augmented to perform with the aid of a priori supplied image cues called markers. The reason for introducing markers is to calibrate a resilient algorithm to oversegmentation. In a hybrid fashion, pixels are first cl ..."
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Cited by 7 (1 self)
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The parallel watershed transformation used in grayscale image segmentation is here augmented to perform with the aid of a priori supplied image cues called markers. The reason for introducing markers is to calibrate a resilient algorithm to oversegmentation. In a hybrid fashion, pixels are first clustered based on spatial proximity and graylevel homogeneity with the watershed transformation. Boundarybased region merging is then effected to condense nonmarked regions into marked catchment basins. The agglomeration strategy works with a weighted neighborhood graph representation of the oversegmented image. The throughput of a parallel Boru # vkalike minimum spanning forest (MSF) operator, applied on the considered graph, embodies the desired image partition, reasoning that all regions in a tree fuse into a homogeneous area containing a unique marker. Two figures of merit of the parallel algorithm are worth mentioning: the local detection of the catchment basins conforming to the watershed principle (which strongly depends on the history of the regions ' growth) and the parallel computation of the Boru # vkalike MSF which merges, at the same time, partial regions, produced by the local labeling, and nonmarked regions to marked basins. Both modules are designed with great concurrency, locality, and reduced software engineering cost, emerging into a scalable algorithm.
Excavator: a computer program for efficiently mining gene expression data
 Nucleic Acids Research
, 2003
"... Massive geneexpression data are generated using microarrays, and clustering geneexpression data is useful for studying functional relationship among genes in a biological process. We have developed a computer package, EXCAVATOR ..."
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Cited by 6 (0 self)
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Massive geneexpression data are generated using microarrays, and clustering geneexpression data is useful for studying functional relationship among genes in a biological process. We have developed a computer package, EXCAVATOR
Connected Spatial Networks over Random Points and a RouteLength Statistic
"... Abstract. We review mathematically tractable models for connected networks on random points in the plane, emphasizing the class of proximity graphs which deserves to be better known to applied probabilists and statisticians. We introduce and motivate a particular statistic R measuring shortness of r ..."
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Cited by 6 (1 self)
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Abstract. We review mathematically tractable models for connected networks on random points in the plane, emphasizing the class of proximity graphs which deserves to be better known to applied probabilists and statisticians. We introduce and motivate a particular statistic R measuring shortness of routes in a network. We illustrate, via Monte Carlo in part, the tradeoff between normalized network length and R in a oneparameter family of proximity graphs. How close this family comes to the optimal tradeoff over all possible networks remains an intriguing open question. The paper is a writeup of a talk developed by the first author during 2007– 2009. Key words and phrases: Proximity graph, random graph, spatial network,
An Autonomous and Decentralized Protocol for Delay Sensitive Overlay Multicast Tree
 Proc. of ICDCS’04
, 2004
"... In this paper, we present a protocol for dynamically maintaining a degreebounded delay sensitive spanning tree in a decentralized way on overlay networks. The protocol aims at repairing the spanning tree autonomously even if multiple nodes ’ leave operations or failures (disappearances) occur simul ..."
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Cited by 6 (3 self)
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In this paper, we present a protocol for dynamically maintaining a degreebounded delay sensitive spanning tree in a decentralized way on overlay networks. The protocol aims at repairing the spanning tree autonomously even if multiple nodes ’ leave operations or failures (disappearances) occur simultaneously or continuously in a specified period. It also aims at maintaining the diameter (maximum delay) of the tree as small as possible. The simulation results using ns2 have shown that the protocol could keep reasonable diameters compared with the existing centralized static algorithm even if many nodes ’ participations and disappearances occur frequently. 1