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87
Globfit: Consistently fitting primitives by discovering global relations
 ACM Trans. on Graphics
"... Figure 1: Starting from a noisy scan, our algorithm recovers the primitive faces along with their global mutual relations, when are then used to produce a final model (all lengths in mm). ..."
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Cited by 44 (14 self)
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Figure 1: Starting from a noisy scan, our algorithm recovers the primitive faces along with their global mutual relations, when are then used to produce a final model (all lengths in mm).
Distributed algorithms for Unidirectional networks
 SIAM J. Comput
, 1993
"... We address the question of distributively computing over a strongly connected unidirectional data communication network. In unidirectional networks the existence of a communication link from one node to another does not imply the existence of a link in the opposite direction. The strong connectiv ..."
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Cited by 33 (3 self)
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We address the question of distributively computing over a strongly connected unidirectional data communication network. In unidirectional networks the existence of a communication link from one node to another does not imply the existence of a link in the opposite direction. The strong connectivity means that from every node there is a directed path to any other node. We assume an arbitrary topology network in which the strong connectivity is the only restriction. Four models are considered: Synchronous and asynchronous, and for each we consider node space availability which grows as either O(1) bits or O(log n) bits per incident link, where n is the total number of nodes in the network. First we provide algorithms for two basic problems in distributed computing in data communication networks, traversal, and election. Each of these basic protocols produces two directed spanning trees rooted at a distinguished node in the network, one called intree, leading to the root, an...
Structuring DepthFirst Search Algorithms in Haskell
, 1995
"... Depthfirst search is the key to a wide variety of graph algorithms. In this paper we express depthfirst search in a lazy functional language, obtaining a lineartime implementation. Unlike traditional imperative presentations, we use the structuring methods of functional languages to construct alg ..."
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Cited by 28 (0 self)
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Depthfirst search is the key to a wide variety of graph algorithms. In this paper we express depthfirst search in a lazy functional language, obtaining a lineartime implementation. Unlike traditional imperative presentations, we use the structuring methods of functional languages to construct algorithms from individual reusable components. This style of algorithm construction turns out to be quite amenable to formal proof, which we exemplify through a calculationalstyle proof of a far from obvious stronglyconnected components algorithm. Classifications: Computing Paradigms (functional programming) ; Environments, Implementations, and Experience (programming, graph algorithms). 1 Introduction The importance of depthfirst search (DFS) for graph algorithms was established twenty years ago by Tarjan (1972) and Hopcroft and Tarjan (1973) in their seminal work. They demonstrated how depthfirst search could be used to construct a variety of efficient graph algorithms. In practice, this...
The Subgraph Homeomorphism Problem
, 1978
"... We investigate the problem of finding a homeomorphlc image of a "pattern " graph H in a larger input graph (3. We view this problem as finding specified sets of edge disjoint or node disjoint paths in (3. Our main result is a linear time algorithm to determine if there exists a simple cycl ..."
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Cited by 20 (0 self)
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We investigate the problem of finding a homeomorphlc image of a "pattern " graph H in a larger input graph (3. We view this problem as finding specified sets of edge disjoint or node disjoint paths in (3. Our main result is a linear time algorithm to determine if there exists a simple cycle containing three given nodes in (3; here H is a triangle, i'4o polynomial time algorithm for this problem was previously known. We also discuss a variety of reductions between related versions of this problem and a number of open problems. I.
Discovering highly reliable subgraphs in uncertain graphs
 In KDD
, 2011
"... In this paper, we investigate the highly reliable subgraph problem, which arises in the context of uncertain graphs. This problem attempts to identify all induced subgraphs for which the probability of connectivity being maintained under uncertainty is higher than a given threshold. This problem ari ..."
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Cited by 15 (1 self)
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In this paper, we investigate the highly reliable subgraph problem, which arises in the context of uncertain graphs. This problem attempts to identify all induced subgraphs for which the probability of connectivity being maintained under uncertainty is higher than a given threshold. This problem arises in a wide range of network applications, such as proteincomplex discovery, network routing, and social network analysis. Since exact discovery may be computationally intractable, we introduce a novel sampling scheme which enables approximate discovery of highly reliable subgraphs with high probability. Furthermore, we transform the core mining task into a new frequent cohesive set problem in deterministic graphs. Such transformation enables the development of an efficient twostage approach which combines novel peeling techniques for maximal set discovery with depthfirst search for further enumeration. We demonstrate the effectiveness and efficiency of the proposed algorithms on real and synthetic data sets.
Object Search by Manipulation
"... Abstract — We investigate the problem of a robot searching for an object. This requires reasoning about both perception and manipulation: certain objects are moved because the target may be hidden behind them and others are moved because they block the manipulator’s access to other objects. We contr ..."
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Abstract — We investigate the problem of a robot searching for an object. This requires reasoning about both perception and manipulation: certain objects are moved because the target may be hidden behind them and others are moved because they block the manipulator’s access to other objects. We contribute a formulation of the object search by manipulation problem using visibility and accessibility relations between objects. We also propose a greedy algorithm and show that it is optimal under certain conditions. We propose a second algorithm which is optimal under all conditions. This algorithm takes advantage of the structure of the visibility and accessibility relations between objects to quickly generate optimal plans. Finally, we demonstrate an implementation of both algorithms on a real robot using a real object detection system. I.
Functional Graph Algorithms with DepthFirst Search (Preliminary Summary)
 in Glasgow Functional Programming Workshop
, 1993
"... Performing a depthfirst search of a graph is one of the fundamental approaches for solving a variety of graph algorithms. Implementing depthfirst search efficiently in a pure functional language has only become possible with the advent of imperative functional programming. In this paper we mix the ..."
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Performing a depthfirst search of a graph is one of the fundamental approaches for solving a variety of graph algorithms. Implementing depthfirst search efficiently in a pure functional language has only become possible with the advent of imperative functional programming. In this paper we mix the techniques of pure functional programming in the same cauldron as depthfirst search to yield a more lucid approach to viewing a variety of graph algorithms. This claim will be illustrated with several examples. 1 Introduction Graph algorithms have long been a challenge to functional programmers. It has not been at all clear how to express such algorithms without using side effects to achieve efficiency. For example, many texts provide implementations of search algorithms which are quadratic in the size of the graph (see [7, 3, 2], for instance), compared with the standard linear implementations given for imperative languages (see [1], for instance). In this paper we implement a variety of ...