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Comparing Reductions to NPComplete Sets
"... Under the assumption that NP does not have pmeasure 0, we investigate reductions to NPcomplete sets and prove the following: 1. Adaptive reductions are more powerful than nonadaptive reductions: there is a problem that is Turingcomplete for NP but not truthtablecomplete. 2. Strong nondetermini ..."
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Cited by 8 (3 self)
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Under the assumption that NP does not have pmeasure 0, we investigate reductions to NPcomplete sets and prove the following: 1. Adaptive reductions are more powerful than nonadaptive reductions: there is a problem that is Turingcomplete for NP but not truthtablecomplete. 2. Strong
Protocol insecurity with finite number of sessions is NPcomplete
 Theoretical Computer Science
, 2001
"... We investigate the complexity of the protocol insecurity problem for a finite number of sessions (fixed number of interleaved runs). We show that this problem is NPcomplete with respect to a DolevYao model of intruders. The result does not assume a limit on the size of messages and supports nonat ..."
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Cited by 183 (12 self)
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We investigate the complexity of the protocol insecurity problem for a finite number of sessions (fixed number of interleaved runs). We show that this problem is NPcomplete with respect to a DolevYao model of intruders. The result does not assume a limit on the size of messages and supports non
Learning Bayesian Networks is NPComplete
, 1996
"... Algorithms for learning Bayesian networks from data havetwo components: a scoring metric and a search procedure. The scoring metric computes a score reflecting the goodnessoffit of the structure to the data. The search procedure tries to identify network structures with high scores. Heckerman e ..."
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Cited by 225 (8 self)
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relative posterior probability greater than a given constant is NPcomplete, when the BDe metric is used. 12.1
Training a 3Node Neural Network is NPComplete
, 1992
"... We consider a 2layer, 3node, ninput neural network whose nodes compute linear threshold functions of their inputs. We show that it is NPcomplete to decide whether there exist weights and thresholds for this network so that it produces output consistent with a given set of training examples. We ..."
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Cited by 227 (3 self)
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We consider a 2layer, 3node, ninput neural network whose nodes compute linear threshold functions of their inputs. We show that it is NPcomplete to decide whether there exist weights and thresholds for this network so that it produces output consistent with a given set of training examples. We
edgedeletion NPcomplete problems
 Conference Record of the Tenth Annual ACM Symposium on Theory of Computing (San Diego, Calif., 1978), ACM
, 1978
"... If ~ is a graph property, the general node(edge) deletion problem can be stated as follows: Find the minimum number of nodes(edges), whose deletion results in a subgraph satisfying property ~. In this paper we show that if ~ belongs to a rather broad class of properties (the class of properties that ..."
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Cited by 90 (0 self)
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that are hereditary on induced subgraphs) then the nodedeletion problem is NPcomplete, and the same is true for several restrictions of it. For the same class of properties, requi~ing the remaining graph to be connected does not change the NPcomplete status of the problem; moreover for a certain subclass, finding
Where the REALLY Hard Problems Are
 IN J. MYLOPOULOS AND R. REITER (EDS.), PROCEEDINGS OF 12TH INTERNATIONAL JOINT CONFERENCE ON AI (IJCAI91),VOLUME 1
, 1991
"... It is well known that for many NPcomplete problems, such as KSat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NPcomplete problems can be summarized by at least one "order parameter", and that the hard p ..."
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Cited by 681 (1 self)
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It is well known that for many NPcomplete problems, such as KSat, etc., typical cases are easy to solve; so that computationally hard cases must be rare (assuming P != NP). This paper shows that NPcomplete problems can be summarized by at least one "order parameter", and that the hard
A Threshold of ln n for Approximating Set Cover
 JOURNAL OF THE ACM
, 1998
"... Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NPhar ..."
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Cited by 778 (5 self)
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Given a collection F of subsets of S = f1; : : : ; ng, set cover is the problem of selecting as few as possible subsets from F such that their union covers S, and max kcover is the problem of selecting k subsets from F such that their union has maximum cardinality. Both these problems are NP
A Comparative Study on Feature Selection in Text Categorization
, 1997
"... This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI), ..."
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Cited by 1294 (15 self)
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This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI
Crozzle: an NPComplete Problem
 In SAC ’97: Proceedings of the 1997 ACM symposium on Applied computing
, 1997
"... At the 1996 Symposium on Applied Computing, it was argued that the RbyC Crozzle problem was NPHard, but not in NP. The original Crozzle problem is a word puzzle that appears, with a cash reward for the highest score, in The Australian Women's Weekly. The RbyC Crozzle problem generalizes the ..."
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Cited by 1 (0 self)
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the original. We argue that both problems are in fact NPComplete. This follows from the reduction of exact 3set cover to RbyC Crozzle and the demonstration of a nondeterministic polynomial time algorithm for solving an arbitrary instance of the RbyC Crozzle problem. A Java implementation
An extended set of Haarlike features for rapid objection detection
 IEEE ICIP
"... Recently Viola et al. [5] have introduced a rapid object detection scheme based on a boosted cascade of simple feature classifiers. In this paper we introduce a novel set of rotated haarlike features. These novel features significantly enrich the simple features of [5] and can also be calculated ef ..."
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Cited by 567 (4 self)
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Recently Viola et al. [5] have introduced a rapid object detection scheme based on a boosted cascade of simple feature classifiers. In this paper we introduce a novel set of rotated haarlike features. These novel features significantly enrich the simple features of [5] and can also be calculated
Results 1  10
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1,917,054