ACM Portal
  Subscribe (Full Service)    Register (Limited Service, Free)    Login
  Search:   The ACM Digital Library   The Guide
  
ACM Home Page
Please provide us with feedback. Feedback
Mining IC test data to optimize VLSI testing
Full text PdfPdf (144 KB)
Source International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining table of contents
Boston, Massachusetts, United States
Pages: 18 - 25  
Year of Publication: 2000
ISBN:1-58113-233-6
Authors
Tony Fountain  San Diego Supercomputer Center, UCSD, 9500 Gilman Dr., La Jolla, CA
Thomas Dietterich  Oregon State University, 303 Dearborn Hall, Corvallis, OR
Bill Sudyka  Hewlett Packard Company, 1000 NE Circle Blvd., Corvallis, OR
Sponsors
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
AAAI : Am Assoc for Artifical Intelligence
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 12,   Downloads (12 Months): 53,   Citation Count: 1
Additional Information:

references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/347090.347099
What is a DOI?

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Cheeseman, P.; Self, M.; Kelly, J.; Taylor, W.; Freeman, D.; and Stutz, J. 1988. Bayesian classification. In Proceedings of the Seventh National Conference on Artificial Intelligence, San Mateo, CA:Morgan Kaufmann 607-611.
 
2
Dempster, A. P.; Laird, N. M.; and Rubin, D. B. 1976. Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society B 39:1- 38.
 
3
Dietterich, T. G. 1997. Machine-Learning research: four current directions. AI Magazine, Menlo Park, CA: AAAI Press 18(4): 97-136.
 
4
Tony Ray Fountain , Thomas G. Dietterich, Just enough die-level test: optimizing ic test via machine learning and decision theory, 1998
 
5
Van Zant, P. 1997. Microchip fabrication: a practical guide to semiconductor processing, third edition. New York: McGraw-Hill.
 
6
Zorich, R. 1991. Handbook of Quality Integrated Circuit Manufacturing. San Diego, CA:Academic Press.

CITED BY
Lior Rokach, Mining manufacturing data using genetic algorithm-based feature set decomposition, International Journal of Intelligent Systems Technologies and Applications, v.4 n.1/2, p.57-78, December 2008

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  B. Hardware
  B.7 INTEGRATED CIRCUITS
      B.7.1 Types and Design Styles
          Subjects: VLSI (very large scale integration)
  B.8 Performance and Reliability

  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.2 Types of Systems
          Subjects: Decision support (e.g., MIS)

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.8 Problem Solving, Control Methods, and Search
          Subjects: Control theory


General Terms:
Algorithms, Design, Experimentation, Management, Measurement, Performance, Theory


Keywords:
EM algorithm, IC test, belief networks, decision theory, real-time control, unsupervised learning

Collaborative Colleagues:
Tony Fountain: colleagues
Thomas Dietterich: colleagues
Bill Sudyka: colleagues

The ACM Portal is published by the Association for Computing Machinery. Copyright © 2009 ACM, Inc.
Terms of Usage   Privacy Policy   Code of Ethics   Contact Us

Useful downloads: Adobe Acrobat    QuickTime    Windows Media Player    Real Player