Accelerated large scale optimization

Details Accelerated large scale optimization Accelerated large scale optimization

2005-11-04

2010-06-01

Trujillo, James (Department: 2159)

Data processing: database and file management or data structures

Database and file access

Preparing data for information retrieval

C707S752000

Reexamination Certificate

active

07730074

ABSTRACT:
A method for efficiently choosing optimal weights in a distributed manner may include optimizing weights in a predefined order while preventing or reducing the likelihood that interacting weights are concurrently optimized. In this manner, divergence and deadlock during optimization may be avoided.

REFERENCES:
patent: 5884077 (1999-03-01), Suzuki
patent: 6006222 (1999-12-01), Culliss
patent: 6014665 (2000-01-01), Culliss
patent: 6078916 (2000-06-01), Culliss
patent: 6182068 (2001-01-01), Culliss
patent: 6539377 (2003-03-01), Culliss
patent: 7222127 (2007-05-01), Bem et al.
patent: 7231399 (2007-06-01), Bem et al.
patent: 2006/0224577 (2006-10-01), Hullender et al.
patent: 2007/0044101 (2007-02-01), Suzuki et al.
“Quickly Generating Billion-Record Synthetic Databases,” Gray, Jim; Sundaresan, Prakash; Englert, Susanne; Baclawski, Ken; Weinberger, Paul; Proceedings of the 1994 ACM SIGMOD international conference on Management of data; pp. 243-252, 1994.
Co-pending U.S. Appl. No. 10/712,263; Jeremy Bem et al.; “Targeting Advertisements Based on Predicted Relevance of the Advertisements”; filed Nov. 14, 2003, 40 pages.
Co-pending U.S. Appl. No. 10/734,584; Jeremy Bem et al.; “Large Scale Machine Learning Systems and Methods”; filed Dec. 15, 2003, 35 pages.
J.H. Friedman, T. Hastie, and R. Tibshirani; “Additive Logistic Regression: a Statistical View of Boosting”; Dept. of Statistics, Stanford University Technical Report; Aug. 20, 1998.
A.Y. Ng and M.I. Jordan; “On Discriminative vs. Generative classifiers: A comparison of logistic regression and naïve Bayes,” in T. Dietterich, S. Becker and Z. Ghahramani (eds.), Advances in Neural Information Processing Systems 14, Cambridge, MA: MIT Press, 2002.
F. Crestani, M. Lalmas, C. Van Rijsbergen and I. Campbell; ““Is This Document Relevant?. . . Probably”: A Survey of Probabilistic Models in Information Retrieval”; ACM Computing Surveys, vol. 30, No. 4, Dec. 1998.
Justin Boyan et al.; “A Machine Learning Architecture for Optimizing Web Search Engines”; Carnegie Mellon University; May 10, 1996; pp. 1-8.
“Click Popularity—DirectHit Technology Overview”; http://www.searchengines.com/directhit.html; Nov. 10, 2003 (print date); 2 pages.
Co-pending U.S. Appl. No. 10/697,333 entitled “Automatic Completion of Fragments of Text”, by Georges R. Harik, et al.; filed Oct. 31, 2003.

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