Saharon Rosset

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The lasso penalizes a least squares regression by the sum of the absolute values (L1-norm) of the coefficients. The form of this penalty encourages sparse solutions (with many coefficients equal to 0).We propose the ‘fused lasso’, a generalization that is designed for problems with features that can be ordered in some meaningful way. The fused lasso(More)
Boosting has been a very successful technique for solving the two-class classification problem. In going from two-class to multi-class classification, most algorithms have been restricted to reducing the multi-class classification problem to multiple two-class problems. In this paper, we develop a new algorithm that directly extends the AdaBoost algorithm(More)
In this paper we study boosting methods from a new perspective. We build on recent work by Efron et al. to show that boosting approximately (and in some cases exactly) minimizes its loss criterion with an l1 constraint on the coefficient vector. This helps understand the success of boosting with early stopping as regularized fitting of the loss criterion.(More)
The quest to explain demographic history during the early part of human evolution has been limited because of the scarce paleoanthropological record from the Middle Stone Age. To shed light on the structure of the mitochondrial DNA (mtDNA) phylogeny at the dawn of Homo sapiens, we constructed a matrilineal tree composed of 624 complete mtDNA genomes from(More)
Mutational events along the human mtDNA phylogeny are traditionally identified relative to the revised Cambridge Reference Sequence, a contemporary European sequence published in 1981. This historical choice is a continuous source of inconsistencies, misinterpretations, and errors in medical, forensic, and population genetic studies. Here, after having(More)
Contemporary Jews comprise an aggregate of ethno-religious communities whose worldwide members identify with each other through various shared religious, historical and cultural traditions. Historical evidence suggests common origins in the Middle East, followed by migrations leading to the establishment of communities of Jews in Europe, Africa and Asia, in(More)
We consider the problem of discovering gene regulatory networks from time-series microarray data. Recently, graphical Granger modeling has gained considerable attention as a promising direction for addressing this problem. These methods apply graphical modeling methods on time-series data and invoke the notion of 'Granger causality' to make assertions on(More)
Estimating the eigenvalues of a population covariance matrix from a sample covariance matrix is a problem of fundamental importance in multivariate statistics; the eigenvalues of covariance matrices play a key role in many widely techniques, in particular in Principal Component Analysis (PCA). In many modern data analysis problems, statisticians are faced(More)