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Comparison of CliqueListing Algorithms
"... This paper compares several published algorithms which list all of the maximal cliques of a graph. A clique is a complete subgraph, i.e., a set of vertices and edges such that every pair of vertices is joined by an edge. A maximal clique is a clique which is not a proper subgraph of a larger clique. ..."
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Cited by 4 (1 self)
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This paper compares several published algorithms which list all of the maximal cliques of a graph. A clique is a complete subgraph, i.e., a set of vertices and edges such that every pair of vertices is joined by an edge. A maximal clique is a clique which is not a proper subgraph of a larger clique
Amortized Efficiency of List Update and Paging Rules
, 1985
"... In this article we study the amortized efficiency of the “movetofront” and similar rules for dynamically maintaining a linear list. Under the assumption that accessing the ith element from the front of the list takes 0(i) time, we show that movetofront is within a constant factor of optimum amo ..."
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Cited by 824 (8 self)
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In this article we study the amortized efficiency of the “movetofront” and similar rules for dynamically maintaining a linear list. Under the assumption that accessing the ith element from the front of the list takes 0(i) time, we show that movetofront is within a constant factor of optimum
Optimal Aggregation Algorithms for Middleware
 IN PODS
, 2001
"... Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape grade, that tells how round it is. For each attribute, there is a sorted list, which lists each object and its grade under ..."
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Cited by 714 (4 self)
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Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape grade, that tells how round it is. For each attribute, there is a sorted list, which lists each object and its grade
Profile Scheduling by List Algorithms
, 1994
"... The notion of profile scheduling was first introduced by Ullman in 1975 in the complexity analysis of deterministic scheduling algorithms. In such a model, the number of processors available to a set of tasks may vary in time. Since the last decade, this model has been used to deal with systems subj ..."
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Cited by 4 (1 self)
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subject to processor failures, multiprogrammed systems, or dynamically reconfigured systems. The aim of this paper is to overview optimal polynomial solutions for scheduling a set of partially ordered tasks in these systems. Particular attentions are given to a class of algorithms referred to as list
Efficient treelisting algorithm
, 1970
"... masking costs and adding to the flexibility of the silicon slices. These 2layer techniques are already in use for other customdesigned integrated circuits. Alternatively, single generalised cells could be interconnected by beam leads on a silica substrate. Multipliers have been proposed3"5 wh ..."
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masking costs and adding to the flexibility of the silicon slices. These 2layer techniques are already in use for other customdesigned integrated circuits. Alternatively, single generalised cells could be interconnected by beam leads on a silica substrate. Multipliers have been proposed3"5 which use the cell shown in Fig. 1 in which the sum output S and carry P are obtained from the binary sum of the inputs B, AD and C. full adder B Fig. 1 Guild6 has proposed a squarerooter, the unit cell of which is shown in Fig. 2. This cell is, effectively, a subtractor, but operates by complementing. Although it is only suggested that this can be used for producing square roots, it is clearly possible to use such a cell as the basis of a general dividing
Learning Decision Lists
, 2001
"... This paper introduces a new representation for Boolean functions, called decision lists, and shows that they are efficiently learnable from examples. More precisely, this result is established for \kDL" { the set of decision lists with conjunctive clauses of size k at each decision. Since k ..."
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Cited by 427 (0 self)
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This paper introduces a new representation for Boolean functions, called decision lists, and shows that they are efficiently learnable from examples. More precisely, this result is established for \kDL" { the set of decision lists with conjunctive clauses of size k at each decision. Since
Arboricity and Bipartite Subgraph Listing Algorithms
, 1994
"... In graphs of bounded arboricity, the total complexity of all maximal complete bipartite subgraphs is O(n). We describe a linear time algorithm to list such subgraphs. The arboricity bound is necessary: for any constant k and any n there exists an nvertex graph with O(n) edges and (n/ log n) k ..."
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Cited by 41 (4 self)
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In graphs of bounded arboricity, the total complexity of all maximal complete bipartite subgraphs is O(n). We describe a linear time algorithm to list such subgraphs. The arboricity bound is necessary: for any constant k and any n there exists an nvertex graph with O(n) edges and (n/ log n) k
SIS: A System for Sequential Circuit Synthesis
, 1992
"... SIS is an interactive tool for synthesis and optimization of sequential circuits. Given a state transition table, a signal transition graph, or a logiclevel description of a sequential circuit, it produces an optimized netlist in the target technology while preserving the sequential inputoutput b ..."
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Cited by 525 (44 self)
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SIS is an interactive tool for synthesis and optimization of sequential circuits. Given a state transition table, a signal transition graph, or a logiclevel description of a sequential circuit, it produces an optimized netlist in the target technology while preserving the sequential input
The FF planning system: Fast plan generation through heuristic search
 Journal of Artificial Intelligence Research
, 2001
"... We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts to be ind ..."
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Cited by 830 (55 self)
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We describe and evaluate the algorithmic techniques that are used in the FF planning system. Like the HSP system, FF relies on forward state space search, using a heuristic that estimates goal distances by ignoring delete lists. Unlike HSP's heuristic, our method does not assume facts
TwoSided Matching: A Study in GameTheoretic Modeling and Analysis
 Econometric Society Monograph Series
, 1990
"... Reading this text on the application of game theory to twosided matching problems, I relived an experience shared by many readers of this journalthe process known as &dquo;resident match.&dquo; At a prescribed moment, over 90 % of senior medical students frantically tear open an envelope ..."
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Cited by 702 (25 self)
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chewing up our preference lists and spitting out one of the more crucial decisions in our lives, some of us sought assurances that the algorithm, named NIMP (the National Intern Matching Program), was fair and just. We were told, or maybe we rationalized, that it was of no use to lie to NIMP.
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