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Journal of the Royal Statistical Society. Series B, Statistical methodology, ISSN 1369-7412, 2014, Volume 76, Issue 2, pp. 373 - 397
Journal Article
Journal of Econometrics, ISSN 0304-4076, 06/2015, Volume 186, Issue 2, pp. 325 - 344
This paper establishes non-asymptotic oracle inequalities for the prediction error and estimation accuracy of the LASSO in stationary vector autoregressive... 
High-dimensional data | Oracle inequality | VAR | Adaptive LASSO | LASSO | REGRESSION | VARIABLE SELECTION | MATHEMATICS, INTERDISCIPLINARY APPLICATIONS | SHRINKAGE | MODEL SELECTION | BRIDGE ESTIMATORS | SOCIAL SCIENCES, MATHEMATICAL METHODS | ECONOMICS
Journal Article
1999, ISBN 9780521593878, xii, 253
Orlando di Lasso was probably the most famous and most popular composer of the second half of the 1500s. This book of essays written by leading scholars from... 
Lasso, Orlando di, 1532-1594 Criticism and interpretation
Book
Journal Article
Journal of computational and graphical statistics, ISSN 1537-2715, 2013, Volume 22, Issue 2, pp. 231 - 245
For high-dimensional supervised learning problems, often using problem-specific assumptions can lead to greater accuracy. For problems with grouped covariates,... 
Model | Regression | Penalize | Nesterov | Regularize | Regularization and the Lasso | STATISTICS & PROBABILITY | REGULARIZATION | SELECTION
Journal Article
Journal of Computational and Graphical Statistics, ISSN 1061-8600, 01/2015, Volume 24, Issue 1, pp. 230 - 253
We consider the problem of learning the structure of a pairwise graphical model over continuous and discrete variables. We present a new pairwise model for... 
Group lasso | Structure learning | Lasso | STATISTICS & PROBABILITY | MULTIVARIATE REGRESSION | SELECTION
Journal Article
Journal Article
Journal Article
1977, Frankfurter Beiträge zur Musikwissenschaft, ISBN 9783795202231, Volume Bd. 7, vii, 169
Book
The Annals of statistics, ISSN 0090-5364, 8/2010, Volume 38, Issue 4, pp. 1978 - 2004
Journal Article
Proceedings of the Royal Society. A, Mathematical, physical, and engineering sciences, ISSN 1471-2946, 2019, Volume 475, Issue 2231, p. 20190578
Network analysis has been applied to various correlation matrix data. Thresholding on the value of the pairwise correlation is probably the most... 
LINKING | thresholding | Lasso | INFORMATION | MULTIDISCIPLINARY SCIENCES | ADAPTIVE LASSO | network inference | sparsity | principle of maximum entropy | SELECTION | LIKELIHOOD
Journal Article
Journal Article
Biometrika, ISSN 0006-3444, 09/2017, Volume 104, Issue 3, pp. 613 - 632
Quantifying the uncertainty in penalized regression under group sparsity is an important open question. We establish, under a high-dimensional scaling, the... 
Significance test | Confidence region | Parametric bootstrap | High-dimensional inference | Group lasso | Sampling distribution | CONFIDENCE-INTERVALS | STATISTICS & PROBABILITY | LASSO ESTIMATORS | INFERENCE | DIMENSIONAL LINEAR-REGRESSION | VARIABLE SELECTION | P-VALUES | MODELS | BIOLOGY | MATHEMATICAL & COMPUTATIONAL BIOLOGY | ADAPTIVE LASSO | Significance
Journal Article
The Annals of statistics, ISSN 0090-5364, 2009, Volume 37, Issue 1, pp. 246 - 270
The Lasso is an attractive technique for regularization and variable selection for high-dimensional data, where the number of predictor variables $p_{n}$ is... 
Approximation | High dimensional spaces | Variable coefficients | Linear regression | Eigenvalues | Signal noise | Mathematical vectors | Estimators | Consistent estimators | Resonance lines | High-dimensional data | Shrinkage estimation | Sparsity | Lasso | REGRESSION | lasso | MODEL SELECTION | high-dimensional data | ADAPTIVE LASSO | STATISTICS & PROBABILITY | sparsity | ASYMPTOTICS | 62F07 | 62J07
Journal Article
Computational Statistics and Data Analysis, ISSN 0167-9473, 02/2015, Volume 82, pp. 207 - 222
The use of the multinomial logit model is typically restricted to applications with few predictors, because in high-dimensional settings maximum likelihood... 
Group Lasso | Logistic regression | Lasso | Multinomial logit model | Variable selection | CATS Lasso | REGRESSION | STATISTICS & PROBABILITY | ALGORITHMS | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | SHRINKAGE | REGULARIZATION | LIKELIHOOD
Journal Article
The Annals of statistics, ISSN 0090-5364, 4/2012, Volume 40, Issue 2, pp. 1198 - 1232
We derive the degrees of freedom of the lasso fit, placing no assumptions on the predictor matrix X. Like the well-known result of Zou, Hastie and Tibshirani... 
Regression coefficients | Degrees of freedom | Gaussian distributions | Linear regression | Inner products | Analytical estimating | Polyhedrons | Mathematical vectors | Matrices | Unbiased estimators | Generalized lasso | High-dimensional | Lasso | PATH | high-dimensional | degrees of freedom | LEAST ANGLE REGRESSION | STATISTICS & PROBABILITY | generalized lasso | VARIABLE SELECTION | 90C46 | 62J07
Journal Article