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558,094
TimeSpace Tradeoffs for Branching Programs
, 1999
"... We obtain the first nontrivial timespace tradeoff lower bound for functions f : {0, 1}^n → {0, 1} on general branching programs by exhibiting a Boolean function f that requires exponential size to be computed by any branching program of length (1 + ε)n, for some constant & ..."
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Cited by 47 (4 self)
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We obtain the first nontrivial timespace tradeoff lower bound for functions f : {0, 1}^n → {0, 1} on general branching programs by exhibiting a Boolean function f that requires exponential size to be computed by any branching program of length (1 + ε)n, for some constant &
An Upper Bound for a Communication Game Related to TimeSpace Tradeoffs
, 1995
"... We prove an unexpected upper bound on a communication game proposed by Jeff Edmonds and Russell Impagliazzo [2, 3] as an approach for proving lower bounds for timespace tradeoffs for branching programs. Our result is based on a generalization of a construction of Erdös, Frankl and Rödl [5] of a lar ..."
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Cited by 4 (0 self)
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We prove an unexpected upper bound on a communication game proposed by Jeff Edmonds and Russell Impagliazzo [2, 3] as an approach for proving lower bounds for timespace tradeoffs for branching programs. Our result is based on a generalization of a construction of Erdös, Frankl and Rödl [5] of a
TimeSpace Tradeoffs, Multiparty Communication Complexity, and NearestNeighbor Problems
 In 34th Symp. on Theory of Computing (STOC’02
, 2002
"... We extend recent techniques for timespace tradeoff lower bounds using multiparty communication complexity ideas. Using these arguments, for inputs from large domains we prove larger tradeoff lower bounds than previously known for general branching programs, yielding time lower bounds of the form T ..."
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Cited by 24 (2 self)
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We extend recent techniques for timespace tradeoff lower bounds using multiparty communication complexity ideas. Using these arguments, for inputs from large domains we prove larger tradeoff lower bounds than previously known for general branching programs, yielding time lower bounds of the form
on Time–Space Tradeoffs for Branching
, 1999
"... We obtain the first nontrivial time–space tradeoff lower bound for functions f: {0, 1}nQ {0, 1} on general branching programs by exhibiting a Boolean function f that requires exponential size to be computed by any branching program of length (1+e) n, for some constant e> 0. We also give the fir ..."
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We obtain the first nontrivial time–space tradeoff lower bound for functions f: {0, 1}nQ {0, 1} on general branching programs by exhibiting a Boolean function f that requires exponential size to be computed by any branching program of length (1+e) n, for some constant e> 0. We also give
TimeSpace Tradeoffs for Satisfiability
 Journal of Computer and System Sciences
, 1997
"... We give the first nontrivial modelindependent timespace tradeoffs for satisfiability. Namely, we show that SAT cannot be solved simultaneously in n 1+o(1) time and n 1\Gammaffl space for any ffl ? 0 on general randomaccess nondeterministic Turing machines. In particular, SAT cannot be solved ..."
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Cited by 37 (1 self)
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We give the first nontrivial modelindependent timespace tradeoffs for satisfiability. Namely, we show that SAT cannot be solved simultaneously in n 1+o(1) time and n 1\Gammaffl space for any ffl ? 0 on general randomaccess nondeterministic Turing machines. In particular, SAT cannot
Space/Time Tradeoffs in Hash Coding with Allowable Errors
 Communications of the ACM
, 1970
"... this paper tradeoffs among certain computational factors in hash coding are analyzed. The paradigm problem considered is that of testing a series of messages onebyone for membership in a given set of messages. Two new hash coding methods are examined and compared with a particular conventional h ..."
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Cited by 2067 (0 self)
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hashcoding method. The computational factors considered are the size of the hash area (space), the time required to identify a message as a nonmember of the given set (reject time), and an allowable error frequency
TimeSpace Tradeoffs Abstract
"... We introduce branching programs augmented with the ability to write to and read from variables other than the inputs. This is a substantial strengthening of the model. We show, however, that Ajtai’s size lower bounds for lineartime multiway branching programs solving a Hamming distance problem [Aj ..."
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We introduce branching programs augmented with the ability to write to and read from variables other than the inputs. This is a substantial strengthening of the model. We show, however, that Ajtai’s size lower bounds for lineartime multiway branching programs solving a Hamming distance problem
Genetic Programming
, 1997
"... Introduction Genetic programming is a domainindependent problemsolving approach in which computer programs are evolved to solve, or approximately solve, problems. Genetic programming is based on the Darwinian principle of reproduction and survival of the fittest and analogs of naturally occurring ..."
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Cited by 1051 (12 self)
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Introduction Genetic programming is a domainindependent problemsolving approach in which computer programs are evolved to solve, or approximately solve, problems. Genetic programming is based on the Darwinian principle of reproduction and survival of the fittest and analogs of naturally occurring
Literate programming
 THE COMPUTER JOURNAL
, 1984
"... The author and his associates have been experimenting for the past several years with a programming language and documentation system called WEB. This paper presents WEB by example, and discusses why the new system appears to be an improvement over previous ones. ..."
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Cited by 549 (3 self)
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The author and his associates have been experimenting for the past several years with a programming language and documentation system called WEB. This paper presents WEB by example, and discusses why the new system appears to be an improvement over previous ones.
Perspectives on Program Analysis
, 1996
"... eing analysed. On the negative side, the semantic correctness of the analysis is seldom established and therefore there is often no formal justification for the program transformations for which the information is used. The semantics based approach [1; 5] is often based on domain theory in the form ..."
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Cited by 678 (35 self)
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eing analysed. On the negative side, the semantic correctness of the analysis is seldom established and therefore there is often no formal justification for the program transformations for which the information is used. The semantics based approach [1; 5] is often based on domain theory
Results 1  10
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558,094