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The Complexity of Generating Test Instances
 IN PROC. STACS'97, LECTURE NOTES IN COMPUTER SCIENCE
, 1997
"... Recently, Watanabe proposed a new framework for testing the correctness and average case behavior of algorithms that purport to solve a given NP search problem efficiently on average. The idea is to randomly generate certified instances in a way that resembles the underlying distribution ¯. We discu ..."
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Cited by 1 (0 self)
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Recently, Watanabe proposed a new framework for testing the correctness and average case behavior of algorithms that purport to solve a given NP search problem efficiently on average. The idea is to randomly generate certified instances in a way that resembles the underlying distribution ¯. We
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 1389 (18 self)
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databases, its performance degrades rapidly with the level of attribute noise in training instances. Therefore, we extended it with a significance test to distinguish noisy instances. This extended algorithm's performance degrades gracefully with increasing noise levels and compares favorably with a
Test instances for the traffic assignment problem
, 2008
"... This short note on the Traffic Assignment Problem (TAP) provides the relevant information on test problems previously used in the literature to facilitate benchmarking. Traffic assignment problem, BPR function, Kleinrock function, linear funcKeywords. tion. Test problems for TAP This short note on ..."
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This short note on the Traffic Assignment Problem (TAP) provides the relevant information on test problems previously used in the literature to facilitate benchmarking. Traffic assignment problem, BPR function, Kleinrock function, linear funcKeywords. tion. Test problems for TAP This short note
Test Instance Generation for Promised NP Search Problems
, 1994
"... . In this paper, we discuss the problem of generating test instances for promised NP search problems. A technical framework is proposed for studying this problem, and it is shown that all known distNPhard search problems are "complete" for test instance generation problems. 1. Introductio ..."
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. In this paper, we discuss the problem of generating test instances for promised NP search problems. A technical framework is proposed for studying this problem, and it is shown that all known distNPhard search problems are "complete" for test instance generation problems. 1
Random Generation of Test Instances for Logic Optimizers
 31st Design Automation Conference (DAC ’94
, 1994
"... Abstract The attempt of using random test circuits for evaluating the performance of logic optimizers like SIS is apparently new. To generate \reasonable " random circuits, we propose the random applications of several transformation rules to an initial circuit instead of the obvious method, ra ..."
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Cited by 20 (2 self)
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Abstract The attempt of using random test circuits for evaluating the performance of logic optimizers like SIS is apparently new. To generate \reasonable " random circuits, we propose the random applications of several transformation rules to an initial circuit instead of the obvious method
Test Instance Construction for NPhard Problems
, 1987
"... The performance of heuristic approximation algorithms for NPhard problems can often only be determined by experimentation. This paper explores some of the issues involved in the efficient generation of useful test sets for such problems, i.e. test sets consisting of instances of the problem for whi ..."
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The performance of heuristic approximation algorithms for NPhard problems can often only be determined by experimentation. This paper explores some of the issues involved in the efficient generation of useful test sets for such problems, i.e. test sets consisting of instances of the problem
1Constructing test instances for Basis Pursuit Denoising
"... Abstract—The number of available algorithms for the socalled Basis Pursuit Denoising problem (or the related LASSOproblem) is large and keeps growing. Similarly, the number of experiments to evaluate and compare these algorithms on different instances is growing. In this note, we present a method ..."
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Abstract—The number of available algorithms for the socalled Basis Pursuit Denoising problem (or the related LASSOproblem) is large and keeps growing. Similarly, the number of experiments to evaluate and compare these algorithms on different instances is growing. In this note, we present a method
Property Testing and its connection to Learning and Approximation
"... We study the question of determining whether an unknown function has a particular property or is fflfar from any function with that property. A property testing algorithm is given a sample of the value of the function on instances drawn according to some distribution, and possibly may query the fun ..."
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Cited by 475 (67 self)
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We study the question of determining whether an unknown function has a particular property or is fflfar from any function with that property. A property testing algorithm is given a sample of the value of the function on instances drawn according to some distribution, and possibly may query
A ReExamination of Text Categorization Methods
, 1999
"... This paper reports a controlled study with statistical significance tests on five text categorization methods: the Support Vector Machines (SVM), a kNearest Neighbor (kNN) classifier, a neural network (NNet) approach, the Linear Leastsquares Fit (LLSF) mapping and a NaiveBayes (NB) classifier. We f ..."
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Cited by 853 (24 self)
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This paper reports a controlled study with statistical significance tests on five text categorization methods: the Support Vector Machines (SVM), a kNearest Neighbor (kNN) classifier, a neural network (NNet) approach, the Linear Leastsquares Fit (LLSF) mapping and a NaiveBayes (NB) classifier. We
Efficient semantic matching
, 2004
"... We think of Match as an operator which takes two graphlike structures and produces a mapping between semantically related nodes. We concentrate on classifications with tree structures. In semantic matching, correspondences are discovered by translating the natural language labels of nodes into prop ..."
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Cited by 855 (68 self)
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into propositional formulas, and by codifying matching into a propositional unsatisfiability problem. We distinguish between problems with conjunctive formulas and problems with disjunctive formulas, and present various optimizations. For instance, we propose a linear time algorithm which solves the first class
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