Sparse inverse covariance estimation with the lasso (2007)
Friedman, Jerome, Hastie, Trevor, Tibshirani, Robert
We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm that...
Pathwise coordinate optimization (2007)
Friedman, Jerome, Hastie, Trevor, Höfling, Holger, Tibshirani, Robert
We consider ``one-at-a-time'' coordinate-wise descent algorithms for a class of convex optimization problems. An algorithm of this kind has been proposed for the $L_1$-penalized regression (lasso) in...
Applications of a new subspace clustering algorithm (COSA) in medical systems biology (2007)
Damian, Doris, Oresic, Matej, Verheij, Elwin, Meulman, Jacqueline, Friedman, Jerome, Adourian, Aram, ...
Metabolomics Vol.3 Nr.1, 69 - 77
Applications of a new subspace clustering algorithm (COSA) in medical systems biology (2007)
Damian, Doris, Oresic, Matej, Verheij, Elwin, Meulman, Jacqueline, Friedman, Jerome, Adourian, Aram, ...
Metabolomics Vol.3 Nr.1, 69 - 77
Discussions of boosting papers, and rejoinders (2004)
Bartlett, Peter L., Bickel, Peter J., Bühlmann, Peter, Freund, Yoav, Friedman, Jerome, Hastie, Trevor, ...
Discussions of: "Process consistency for AdaBoost" [Ann. Statist. 32 (2004), no. 1, 13-29] by W. Jiang; "On the Bayes-risk consistency of regularized boosting methods" [ibid., 30-55] by G. Lugosi and...
Xiaoming Huo, Ana Georgina Flesia, Bob Muise, Robert Stanfill, Jerome Friedman, Bogdan Popescu, ...
In target recogni2BU appli2BU--; of di;U--;A2BU t or classiA2BU--; analysi2 each `feature'i s a result of a convoluti; of aniA--D#R wi-- a filter,whi h may bederi ed from a feature vector. Iti si--...
Information Retrieval Using Statistical Classification (2000)
David A. Hull, Jerome Friedman
In the classical information retrieval (IR) problem, the system must find all documents in a collection that are related to a topic defined by a user's query. A common approach to the IR problem is...
Friedman, Jerome, Hastie, Trevor, Tibshirani, Robert
Boosting is one of the most important recent developments in classification methodology. Boosting works by sequentially applying a classification algorithm to reweighted versions of the training data...
Additive Logistic Regression: a Statistical View of Boosting (1999)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often...
Additive Logistic Regression: a Statistical View of Boosting (1998)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1995) is one of the most important recent developments in classification methodology. Boosting works by sequentially applying a classification algorithm to reweighted...
AFCRL FACILITIES OPERATION. (1998)
Two PIN diode detectors were developed for monitoring bremsstrahlung and electron radiation environments. The detectors were calibrated against LiF thermoluminescent dosimeters (TLD). A lithium...
Additive Logistic Regression: a Statistical View of Boosting (1998)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often...
Additive Logistic Regression: a Statistical View of Boosting (1998)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms can often...
Additive Logistic Regression: a Statistical View of Boosting (1998)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms often can...
Additive Logistic Regression: a Statistical View of Boosting (1998)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms often can...
Additive Logistic Regression: a Statistical View of Boosting (1998)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms often can...
Additive Logistic Regression: a Statistical View of Boosting (1998)
Jerome Friedman, Trevor Hastie, Robert Tibshirani
Boosting (Freund & Schapire 1996, Schapire & Singer 1998) is one of the most important recent developments in classification methodology. The performance of many classification algorithms often can...
UMI #88-28,178.
Qualifying paper--Harvard Graduate School of Education, 1986.
Michael Servetus : the theology of optimism / (1971)
Thesis--University of Wisconsin.
Jerome Friedman, Trevor Hastie, Yoav Freund, Robert E. Schapire
this paper is in establishing a connection between boosting, a newcomer to the statistics scene, and additive models.
Chicago's rail passenger and freight terminals problem. (1961)
Thesis (M.B.A.)--Indiana University, 1961.