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A Survey of Image Registration Techniques
 ACM Computing Surveys
, 1992
"... Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors or from different viewpoints. Over the years, a broad range of techniques have been developed for the various types of data and problems. These ..."
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Cited by 979 (2 self)
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of distortions are distinguished. The first type are those which are the source of misregistration, i.e., they are the cause of the misalignment between the two images. Distortions which are the source of misregistration determine the transformation class which will optimally align the two images
Planning as heuristic search,
 5 – 33, ISSN
, 2001
"... Abstract In the AIPS98 Planning Contest, the HSP planner showed that heuristic search planners can be competitive with stateoftheart Graphplan and SAT planners. Heuristic search planners like HSP transform planning problems into problems of heuristic search by automatically extracting heuristics ..."
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Cited by 421 (33 self)
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Abstract In the AIPS98 Planning Contest, the HSP planner showed that heuristic search planners can be competitive with stateoftheart Graphplan and SAT planners. Heuristic search planners like HSP transform planning problems into problems of heuristic search by automatically extracting
The Protein Threading Problem With Sequence Amino Acid Interaction Preferences Is NPComplete
 Protein Eng
, 1995
"... In recent protein structure prediction research there has been a great deal of interest in using amino acid interaction preferences (e.g., contact potentials, or potentials of mean force) to align ("thread") a protein sequence to a known structural motif. An important open question is whet ..."
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Cited by 122 (4 self)
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function. We prove that if both these conditions are allowed, then the Protein Threading Decision Problem (does there exist a threading with a score less than K?) is NPcomplete (in the strong sense, i.e., is not merely a number problem), and the related problem of finding the globally optimal protein
Nearoptimal sensor placements in gaussian processes
 In ICML
, 2005
"... When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to address this task, for example, geometry or disk models, placing sensors at the points of highest entropy (variance) in t ..."
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Cited by 342 (34 self)
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information is NPcomplete. To address this issue, we describe a polynomialtime approximation that is within (1 − 1/e) of the optimum by exploiting the submodularity of mutual information. We also show how submodularity can be used to obtain online bounds, and design branch and bound search procedures. We
System Design is an NPComplete Problem
 Systems Engineering
, 2001
"... The system design process translates the customers ’ needs into a buildable system design. It requires selecting subsystems from an allowable set and matching the interfaces between them. Designs that meet the toplevel input and output requirements are tested to see how well they meet the system’s ..."
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Cited by 5 (1 self)
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performance and cost goals. This paper proves that the System Design Problem is NPcomplete by reduction from the Knapsack Problem, which is known to be NPcomplete. The implication of this proof is that designing optimal systems with deterministic, polynomial time procedures is not possible
Two NPComplete Augmentation Problems
, 1997
"... We prove that the Simplicity Preserving EdgeConnectivity Augmentation Problem and the problem of Increasing EdgeConnectivity by Reinforcing Edges are NPcomplete. 1 Introduction The kedgeconnectivity augmentation problem is to find a smallest set F of new edges which makes a given (di)graph G ..."
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Cited by 6 (4 self)
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We prove that the Simplicity Preserving EdgeConnectivity Augmentation Problem and the problem of Increasing EdgeConnectivity by Reinforcing Edges are NPcomplete. 1 Introduction The kedgeconnectivity augmentation problem is to find a smallest set F of new edges which makes a given (di)graph G
PolynomialTime Reductions, NPCompleteness, and Approximations
"... This course will cover some basic topics in the design and analysis of approximation algorithms. The study of approximation algorithms has developed from the seeming intractability of a number of widelyapplicable NPhard optimization problems. These optimization problems are unlikely to admit eff ..."
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This course will cover some basic topics in the design and analysis of approximation algorithms. The study of approximation algorithms has developed from the seeming intractability of a number of widelyapplicable NPhard optimization problems. These optimization problems are unlikely to admit
Complexity Measures and Decision Tree Complexity: A Survey
 Theoretical Computer Science
, 2000
"... We discuss several complexity measures for Boolean functions: certificate complexity, sensitivity, block sensitivity, and the degree of a representing or approximating polynomial. We survey the relations and biggest gaps known between these measures, and show how they give bounds for the decision tr ..."
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Cited by 197 (17 self)
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versus NP problem: for all NPcomplete problems the current upper and lower bounds lie exponentially ...
Interpretations of the Quantum Theory and NPComplete Problems
"... In this paper, we show that the satisfiability problem (SAT, for short) can be solved by a quantum Turing machine in O(2 n 4 ) time under an assumption that a superposed physical states can be observed without collapsing the superposition, where n is the total length of the description of an inpu ..."
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of an input logical formula f and the description of the number of variables in f . Furthermore, we show that any NPcomplete problem can be solved in polynomial time under a stronger assumption. These assumptions are not widely supported in current quantum physics, however, very recently, Aharonov et al. [1
Using Neural Networks and Genetic Algorithms as Heuristics for NPComplete Problems
, 1983
"... Paradigms for using neural networks (NNs) and genetic algorithms (GAs) to heuristically solve boolean satisfiability (SAT) problems are presented. Since SAT is NPComplete, any other NPComplete problem can be transformed into an equivalent SAT problem in polynomial time, and solved via either parad ..."
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Cited by 18 (8 self)
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Paradigms for using neural networks (NNs) and genetic algorithms (GAs) to heuristically solve boolean satisfiability (SAT) problems are presented. Since SAT is NPComplete, any other NPComplete problem can be transformed into an equivalent SAT problem in polynomial time, and solved via either
Results 1  10
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