Results 1  10
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406,411
WorstCase Upper Bounds for MAX2SAT with an Application to MAXCUT
, 2001
"... The maximum 2satisfiability problem (MAX2SAT) is: given a Boolean formula in 2CNF, find a truth assignment that satisfi es the maximum possible number of its clauses. MAX2SAT is MAXSNPcomplete. Recently, this problem received much attention in the contexts of (polynomialtime) approximation ..."
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Cited by 27 (2 self)
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. This bound implies the bound poly(L) 2 . Our results significantly improve previous bounds: poly(L) 2 [30] and poly(L) 2 (implicit in [4]).
New WorstCase Upper Bounds for MAX2SAT with Application to MAXCUT
, 2000
"... The maximum 2satisfiability problem (MAX2SAT) is: given a Boolean formula in 2CNF, find a truth assignment that satisfies the maximum possible number of its clauses. MAX2SAT is MAXSNPcomplete. Recently, this problem received much attention in the contexts of approximation (polynomialtime) a ..."
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Cited by 21 (7 self)
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poly(L) 2^(L/10). Our results significantly improve previous bounds: poly(L) 2^(K/2.88) [30] and poly(L) 2^(K/3.44) (implicit in [4]). As an application, we derive upper bounds for the (MAXSNPcomplete) maximum cut problem (MAXCUT), showing that it can be solved in time poly(M) 2^(M/3), where M
Worstcase equilibria
 IN PROCEEDINGS OF THE 16TH ANNUAL SYMPOSIUM ON THEORETICAL ASPECTS OF COMPUTER SCIENCE
, 1999
"... In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a ver ..."
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Cited by 847 (17 self)
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In a system in which noncooperative agents share a common resource, we propose the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. Deriving upper and lower bounds for this ratio in a model in which several agents share a
New methods for 3SAT decision and worstcase analysis
 THEORETICAL COMPUTER SCIENCE
, 1999
"... We prove the worstcase upper bound 1:5045 n for the time complexity of 3SAT decision, where n is the number of variables in the input formula, introducing new methods for the analysis as well as new algorithmic techniques. We add new 2 and 3clauses, called "blocked clauses", generali ..."
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Cited by 73 (14 self)
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We prove the worstcase upper bound 1:5045 n for the time complexity of 3SAT decision, where n is the number of variables in the input formula, introducing new methods for the analysis as well as new algorithmic techniques. We add new 2 and 3clauses, called "blocked clauses
Algorithms for SAT and Upper Bounds on Their Complexity
, 2001
"... We survey recent algorithms for the propositional satisfiability problem, in particular algorithms that have the best current worstcase upper bounds on their complexity. We also discuss some related issues: the derandomization of the algorithm of Paturi, Pudlák, Saks and Zane, the ValiantVazirani ..."
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Cited by 10 (2 self)
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We survey recent algorithms for the propositional satisfiability problem, in particular algorithms that have the best current worstcase upper bounds on their complexity. We also discuss some related issues: the derandomization of the algorithm of Paturi, Pudlák, Saks and Zane, the Valiant
WorstCase Analysis of the Perceptron and Exponentiated Update Algorithms
 Artificial Intelligence
, 1998
"... The absolute loss is the absolute difference between the desired and predicted outcome. This paper demonstrates worstcase upper bounds on the absolute loss for the Perceptron learning algorithm and the Exponentiated Update learning algorithm, which is related to the Weighted Majority algorithm. The ..."
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Cited by 10 (1 self)
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The absolute loss is the absolute difference between the desired and predicted outcome. This paper demonstrates worstcase upper bounds on the absolute loss for the Perceptron learning algorithm and the Exponentiated Update learning algorithm, which is related to the Weighted Majority algorithm
WorstCase Absolute Loss Bounds for Linear Learning Algorithms
 In Proc. Tenth Annual Conf. on Computational Learning Theory
, 1997
"... The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrate worstcase upper bounds on the absolute loss for the perceptron algorithm and an exponentiated update algorithm related to the Weighted Majority algorithm. The bounds characterize the behavior of th ..."
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Cited by 2 (1 self)
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The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrate worstcase upper bounds on the absolute loss for the perceptron algorithm and an exponentiated update algorithm related to the Weighted Majority algorithm. The bounds characterize the behavior
On Delivery Guarantees and WorstCase Forwarding . . .
, 2010
"... In this paper, we provide a thorough theoretical study on delivery guarantees, loopfree operation, and worstcase behavior of face and combined greedyface routing. We show that under specific planar topology control schemes, recovery from a greedy routing failure is always possible without changi ..."
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Cited by 6 (2 self)
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loopfree operation. For those variants, we derive worstcase upper bounds on the number of forwarding steps.
Local Search Algorithms for SAT: WorstCase Analysis
 In: Proceedings of the 6th Scandinavian Workshop on Algorithm Theory, LNCS 1432
, 1998
"... Recent experiments demonstrated that local search algorithms (e.g. GSAT) are able to find satisfying assignments for many "hard" Boolean formulas. However, no nontrivial worstcase upper bounds were proved, although many such bounds of the form 2 ffn (ff ! 1 is a constant) are known for ..."
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Cited by 3 (3 self)
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Recent experiments demonstrated that local search algorithms (e.g. GSAT) are able to find satisfying assignments for many "hard" Boolean formulas. However, no nontrivial worstcase upper bounds were proved, although many such bounds of the form 2 ffn (ff ! 1 is a constant) are known
Results 1  10
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406,411