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WorstCase Running Times for AverageCase Algorithms
"... Abstract—Under a standard hardness assumption we exactly characterize the worstcase running time of languages that are in average polynomialtime over all polynomialtime samplable distributions. More precisely we show that if exponential time is not infinitely often in subexponential space, then t ..."
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Cited by 3 (0 self)
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Abstract—Under a standard hardness assumption we exactly characterize the worstcase running time of languages that are in average polynomialtime over all polynomialtime samplable distributions. More precisely we show that if exponential time is not infinitely often in subexponential space
Worstcase and Averagecase Approximations by Simple Randomized Search Heuristics
 In Proc. of STACS ’05, volume 3404 of LNCS
, 2005
"... Abstract. In recent years, probabilistic analyses of algorithms have received increasing attention. Despite results on the averagecase complexity and smoothed complexity of exact deterministic algorithms, little is known about the averagecase behavior of randomized search heuristics (RSHs). In thi ..."
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Cited by 49 (11 self)
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). In this paper, two simple RSHs are studied on a simple scheduling problem. While it turns out that in the worst case, both RSHs need exponential time to create solutions being significantly better than 4/3approximate, an averagecase analysis for two input distributions reveals that one RSH is convergent
AverageCase Intractability vs. WorstCase Intractability
 IN THE 23RD INTERNATIONAL SYMPOSIUM ON MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE
, 1998
"... We use the assumption that all sets in NP (or other levels of the polynomialtime hierarchy) have efficient averagecase algorithms to derive collapse consequences for MA, AM, and various subclasses of P/poly. As a further consequence we show for C 2 fP(PP);PSPACEg that C is not tractable in the a ..."
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Cited by 3 (1 self)
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We use the assumption that all sets in NP (or other levels of the polynomialtime hierarchy) have efficient averagecase algorithms to derive collapse consequences for MA, AM, and various subclasses of P/poly. As a further consequence we show for C 2 fP(PP);PSPACEg that C is not tractable
WorstCase Optimal and AverageCase Efficient Geometric AdHoc Routing
, 2003
"... In this paper we present GOAFR, a new geometric adhoc routing algorithm combining greedy and face routing. We evaluate this algorithm by both rigorous analysis and comprehensive simulation. GOAFR is the first adhoc algorithm to be both asymptotically optimal and averagecase e#cient. For our simul ..."
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Cited by 238 (11 self)
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In this paper we present GOAFR, a new geometric adhoc routing algorithm combining greedy and face routing. We evaluate this algorithm by both rigorous analysis and comprehensive simulation. GOAFR is the first adhoc algorithm to be both asymptotically optimal and averagecase e#cient. For our
WorstCase Vs. Algorithmic AverageCase Complexity in the PolynomialTime Hierarchy
 In Proceedings of the 10th International Workshop on Randomization and Computation, RANDOM 2006
, 2006
"... We show that for every integer k> 1, if Σk, the k’th level of the polynomialtime hierarchy, is worstcase hard for probabilistic polynomialtime algorithms, then there is a language L ∈ Σk such that for every probabilistic polynomialtime algorithm that attempts to decide it, there is a samplabl ..."
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Cited by 2 (1 self)
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We show that for every integer k> 1, if Σk, the k’th level of the polynomialtime hierarchy, is worstcase hard for probabilistic polynomialtime algorithms, then there is a language L ∈ Σk such that for every probabilistic polynomialtime algorithm that attempts to decide it, there is a
Q : Worstcase Fair Weighted Fair Queueing
"... The Generalized Processor Sharing (GPS) discipline is proven to have two desirable properties: (a) it can provide an endtoend boundeddelay service to a session whose traffic is constrained by a leaky bucket; (b) it can ensure fair allocation of bandwidth among all backlogged sessions regardless o ..."
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Cited by 365 (11 self)
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approximation algorithms of GPS have been proposed. Among these, Weighted Fair Queueing (WFQ) also known as Packet Generalized Processor Sharing (PGPS) has been considered to be the best one in terms of accuracy. In particular, it has been proven that the delay bound provided by WFQ is within one packet
A NEW POLYNOMIALTIME ALGORITHM FOR LINEAR PROGRAMMING
 COMBINATORICA
, 1984
"... We present a new polynomialtime algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than the ell ..."
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Cited by 860 (3 self)
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We present a new polynomialtime algorithm for linear programming. In the worst case, the algorithm requires O(tf'SL) arithmetic operations on O(L) bit numbers, where n is the number of variables and L is the number of bits in the input. The running,time of this algorithm is better than
the Deutsche Forschungsgemeinschaft. WorstCase and AverageCase Approximations by Simple Randomized Search Heuristics
, 2004
"... Abstract. In recent years, probabilistic analyses of algorithms have received increasing attention. Despite results on the averagecase complexity and smoothed complexity of exact deterministic algorithms, little is known on the averagecase behavior of randomized search heuristics (RSHs). In this p ..."
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). In this paper, two simple RSHs are studied on a simple scheduling problem. While it turns out that in the worst case, both RSHs need exponential time to create solutions being significantly better than 4/3approximate, an averagecase analysis for two input distributions reveals that one RSH is convergent
A Learning Algorithm for Continually Running Fully Recurrent Neural Networks
, 1989
"... The exact form of a gradientfollowing learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a precis ..."
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Cited by 534 (4 self)
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The exact form of a gradientfollowing learning algorithm for completely recurrent networks running in continually sampled time is derived and used as the basis for practical algorithms for temporal supervised learning tasks. These algorithms have: (1) the advantage that they do not require a
Fibonacci Heaps and Their Uses in Improved Network optimization algorithms
, 1987
"... In this paper we develop a new data structure for implementing heaps (priority queues). Our structure, Fibonacci heaps (abbreviated Fheaps), extends the binomial queues proposed by Vuillemin and studied further by Brown. Fheaps support arbitrary deletion from an nitem heap in qlogn) amortized tim ..."
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Cited by 739 (18 self)
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time and all other standard heap operations in o ( 1) amortized time. Using Fheaps we are able to obtain improved running times for several network optimization algorithms. In particular, we obtain the following worstcase bounds, where n is the number of vertices and m the number of edges
Results 1  10
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21,807