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1,579,154
Instance Complexity
, 1994
"... We introduce a measure for the computational complexity of individual instances of a decision problem and study some of its properties. The instance complexity of a string x with respect to a set A and time bound t, ic t (x : A), is defined as the size of the smallest specialcase program for A that ..."
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Cited by 32 (1 self)
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We introduce a measure for the computational complexity of individual instances of a decision problem and study some of its properties. The instance complexity of a string x with respect to a set A and time bound t, ic t (x : A), is defined as the size of the smallest specialcase program for A
On ResourceBounded Instance Complexity
 Theoretical Computer Science A
, 1995
"... The instance complexity of a string x with respect to a set A and time bound t, ic t (x : A), is the length of the shortest program for A that runs in time t, decides x correctly, and makes no mistakes on other strings (where "don't know" answers are permitted). The Instance Complexit ..."
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Cited by 18 (9 self)
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The instance complexity of a string x with respect to a set A and time bound t, ic t (x : A), is the length of the shortest program for A that runs in time t, decides x correctly, and makes no mistakes on other strings (where "don't know" answers are permitted). The Instance
Instance Complexity of NPhard sets
, 1999
"... Instance complexity was introduced by Orponen, Ko, Schöning, and Watanabe [7, 14, 15] as a measure of the complexity of individual instances of a decision problem. Comparing instance complexity to Kolmogorov complexity (i.e. the inherent complexity of a string), they introduced the notion of ph ..."
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Instance complexity was introduced by Orponen, Ko, Schöning, and Watanabe [7, 14, 15] as a measure of the complexity of individual instances of a decision problem. Comparing instance complexity to Kolmogorov complexity (i.e. the inherent complexity of a string), they introduced the notion of p
Instancebased learning algorithms
 Machine Learning
, 1991
"... Abstract. Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms that learn decision trees, classification rules, and distributed networks. However, no investigation has analyzed algorithms that use only specific instances to ..."
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Cited by 1359 (18 self)
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Abstract. Storing and using specific instances improves the performance of several supervised learning algorithms. These include algorithms that learn decision trees, classification rules, and distributed networks. However, no investigation has analyzed algorithms that use only specific instances
Toward an instance theory of automatization
 Psychological Review
, 1988
"... This article presents a theory in which automatization is construed as the acquisition of a domainspecific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur ..."
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Cited by 613 (37 self)
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This article presents a theory in which automatization is construed as the acquisition of a domainspecific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur
Nondeterministic communication complexity and instance complexity
"... Abstract. We study the relationship between nondeterministic communication complexity [8, 9, 4] and instance complexity [7]. For that purpose, the witness of the nondeterministic communication protocol executed by Alice and Bob is interpreted by Alice as a program p that, for t sufficiently large, ..."
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Abstract. We study the relationship between nondeterministic communication complexity [8, 9, 4] and instance complexity [7]. For that purpose, the witness of the nondeterministic communication protocol executed by Alice and Bob is interpreted by Alice as a program p that, for t sufficiently large
Nondeterministic Instance Complexity and HardtoProve Tautologies
"... In this note we rst formalize the notion of hard tautologies using a nondeterministic generalization of instance complexity. We then show, under reasonable complexitytheoretic assumptions, that there are innitely many propositional tautologies that are hard to prove in any sound propositional p ..."
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Cited by 3 (2 self)
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In this note we rst formalize the notion of hard tautologies using a nondeterministic generalization of instance complexity. We then show, under reasonable complexitytheoretic assumptions, that there are innitely many propositional tautologies that are hard to prove in any sound propositional
Nondeterministic instance complexity and proof systems with advice
 In Proc. 3rd International Conference on Language and Automata Theory and Applications, volume 5457 of Lecture Notes in Computer Science
"... Abstract. Motivated by strong KarpLipton collapse results in bounded arithmetic, Cook and Krajíček [7] have recently introduced the notion of propositional proof systems with advice. In this paper we investigate the following question: Do there exist polynomially bounded proof systems with advice f ..."
Parameterized Complexity
, 1998
"... the rapidly developing systematic connections between FPT and useful heuristic algorithms  a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs ..."
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Cited by 1218 (75 self)
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the rapidly developing systematic connections between FPT and useful heuristic algorithms  a new and exciting bridge between the theory of computing and computing in practice. The organizers of the seminar strongly believe that knowledge of parameterized complexity techniques and results belongs
Monotone Complexity
, 1990
"... We give a general complexity classification scheme for monotone computation, including monotone spacebounded and Turing machine models not previously considered. We propose monotone complexity classes including mAC i , mNC i , mLOGCFL, mBWBP , mL, mNL, mP , mBPP and mNP . We define a simple ..."
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Cited by 2837 (11 self)
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We give a general complexity classification scheme for monotone computation, including monotone spacebounded and Turing machine models not previously considered. We propose monotone complexity classes including mAC i , mNC i , mLOGCFL, mBWBP , mL, mNL, mP , mBPP and mNP . We define a
Results 1  10
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1,579,154