NDLI: On the fine structure of large search spaces

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Table of contents

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Face detection and its applications in intelligent and focused image retrieval

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Spatial color histograms for content-based image retrieval

Efficiently detecting arbitrary shaped clusters in image databases

On the fine structure of large search spaces

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Solving hard satisfiability problems: a unified algorithm based on discrete Lagrange multipliers

Removing node and edge overlapping in graph layouts by a modified EGENET solver

SAMON: communication, cooperation and learning of mobile autonomous robotic agents

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Monitoring of aircraft operation using statistics and machine learning

Controlled flux results in stable decision trees

Mobile robotics planning using abstract Markov decision processes

A new GA approach for the vehicle routing problem

A dynamic scheduling benchmark: design, implementation and performance evaluation

A generic task strategy for solving routine decision making problems

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Neurofuzzy approaches for advance hearing devices

Signal trend identification with fuzzy methods

On the use of genetic algorithms in database client clustering

Autonomous filter engine based on knowledge acquisition from the Web

Capturing user access patterns in the Web for data mining

Query reification based approach for object-oriented query formulation aid

Search strategies for hybrid search spaces

Fast and efficient searching of multimedia databases using holographic memory

Box consistency through weak box consistency

Constrained simulated annealing with applications in nonlinear continuous constrained global optimization

Ontology based personalized search

Dynamic email organization via relevance categories

A new study on using HTML structures to improve retrieval

Learning to identify interesting links in intelligent information discovery

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On the sufficiency of limited testing for knowledge based systems

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On the fine structure of large search spaces

Content Provider	IEEE Xplore Digital Library
Author	Gomes, C. Selman, B.
Copyright Year	1999
Description	Author affiliation: Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA (Gomes, C.)
Abstract	Recently, there has been significant progress in our understanding of the computational nature of combinatorial problems. Randomized search methods, both complete and incomplete, often outperform deterministic strategies. In this paper, we relate the performance of randomized methods to the geometric properties of the underlying search space. In particular, our study reveals the inherent fractal nature of the search space at different-length scales, for a range of combinatorial problems. We also discuss the impact of these results on the design of better search methods.
Starting Page	197
Ending Page	201
File Size	263634
Page Count	5
File Format	PDF
ISBN	0769504566
ISSN	10823409
DOI	10.1109/TAI.1999.809786
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-11-09
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Runtime Search methods Concrete Computer science Search problems Fractals Costs
Content Type	Text
Resource Type	Article

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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