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Biometrika, ISSN 0006-3444, 03/2018, Volume 105, Issue 1, pp. 1 - 18
Summary  We propose dual regression as an alternative to quantile regression for the global estimation of conditional distribution functions... 
Duality | Quantile regression | Convex approximation | Method of moments | Monotonicity | Mathematical programming | BIOLOGY | MATHEMATICAL & COMPUTATIONAL BIOLOGY | STATISTICS & PROBABILITY | INFERENCE | CURVES | Economic models | Scale models | Regression | Mathematical models | Regression analysis | Distribution functions
Journal Article
Biostatistics, ISSN 1465-4644, 07/2015, Volume 16, Issue 2, pp. 326 - 338
Journal Article
The Annals of Statistics, ISSN 0090-5364, 6/2010, Volume 38, Issue 3, pp. 1287 - 1319
.... We describe a method based on ℓ₁-regularized logistic regression, in which the neighborhood of any given node is estimated by performing logistic regression subject to an ℓ₁-constraint... 
Logistic regression | Sample size | Machine learning | Ising model | Markov models | Modeling | Consistent estimators | Vertices | Fisher information | Estimation methods | ℓ1-regularization | Graphical models | Structure learning | Model selection | High-dimensional asymptotics | Convex risk minimization | Markov random fields | 68T99 | convex risk minimization | high-dimensional asymptotics | model selection | 62F12 | structure learning | ℓ_1-regularization
Journal Article
by She, Y and Chen, K
Biometrika, ISSN 0006-3444, 09/2017, Volume 104, Issue 3, pp. 633 - 647
In high-dimensional multivariate regression problems, enforcing low rank in the coefficient matrix offers effective dimension reduction, which greatly facilitates parameter estimation and model interpretation... 
Robust estimation | Non-asymptotic analysis | Sparsity | Low-rank matrix approximation | CONVEX RELAXATION | ALGORITHM | STATISTICS & PROBABILITY | GENERALIZED LINEAR-MODELS | VARIABLE SELECTION | NUCLEAR-NORM PENALIZATION | OPTIMAL RATES | ESTIMATORS | MATRICES | BIOLOGY | MATHEMATICAL & COMPUTATIONAL BIOLOGY
Journal Article
IEEE Transactions on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, 01/2017, Volume 39, Issue 1, pp. 156 - 171
Journal Article
IEEE Transactions on Information Theory, ISSN 0018-9448, 01/2013, Volume 59, Issue 1, pp. 482 - 494
Journal Article
Journal of Computational and Graphical Statistics, ISSN 1061-8600, 01/2014, Volume 23, Issue 1, pp. 192 - 210
.... Our approach generalizes and subsumes the well-known work of Barlow and Brunk on fitting isotonic regressions subject to specially structured loss functions, and expands the range of loss functions that can be used (e.g... 
Convex optimization | Regularization path | Nonparametric regression | Datasets | Integers | Outliers | Isotonic solutions | Algorithms | Optimal solutions | Iterative solutions | Regression analysis | Simulation training | Isotonicity | Regression Methods | ALGORITHM | CHAIN CONSTRAINTS | STATISTICS & PROBABILITY | RULE | CONVEX-FUNCTIONS SUBJECT
Journal Article
Annals of Statistics, ISSN 0090-5364, 06/2017, Volume 45, Issue 3, pp. 991 - 1023
Kernel ridge regression (KRR) is a standard method for performing non-parametric regression over reproducing kernel Hilbert spaces... 
Dimensionality reduction | Random projection | Convex optimization | Nonparametric regression | Kernel method | MATRIX | RATES | dimensionality reduction | kernel method | convex optimization | CONVEX-PROGRAMS | STATISTICS & PROBABILITY | ALGORITHMS | random projection
Journal Article
Journal Article
Biometrics, ISSN 0006-341X, 12/2018, Volume 74, Issue 4, pp. 1331 - 1340
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 01/2018, Volume 27, Issue 1, pp. 24 - 37
... of them. The provably most robust methods to identify these conic basis columns are based on nonnegative sparse regression and self-dictionaries, and require the solution of large-scale convex optimization problems... 
Gradient methods | Dictionaries | pure-pixel assumption | Nonnegative matrix factorization | sparse regression | Sparse matrices | self dictionary | separability | fast gradient | Robustness | Convex functions | Data models | Hyperspectral imaging | hyperspectral imaging | ALGORITHM | MATRIX FACTORIZATION | SEPARATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Usage | Research | Computer simulation | Convex programming
Journal Article
Annals of Statistics, ISSN 0090-5364, 12/2017, Volume 45, Issue 6, pp. 2400 - 2426
Journal Article
Journal Article
Computational Statistics and Data Analysis, ISSN 0167-9473, 09/2012, Volume 56, Issue 9, pp. 2729 - 2741
Journal Article
Machine Learning, ISSN 0885-6125, 7/2002, Volume 48, Issue 1, pp. 253 - 285
Journal Article
Journal of the American Statistical Association, ISSN 0162-1459, 01/2019, Volume 114, Issue 525, pp. 318 - 331
Journal Article
ANNALS OF STATISTICS, ISSN 0090-5364, 06/2019, Volume 47, Issue 3, pp. 1554 - 1584
In this paper, we present a general convex optimization approach for solving high-dimensional multiple response tensor regression problems under low-dimensional structural assumptions... 
Tensor regression | BOUNDS | intrinsic dimension | low-rank | convex regularization | STATISTICS & PROBABILITY | sparsity | Gaussian width | SELECTION
Journal Article
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