High Dimensional Robust Sparse Regression

Media Summary: Constantine Caramanis (University of Texas at Austin) ... CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 03, 2020 by the ... Po-Ling Loh (University of Wisconsin, Madison) ...

High Dimensional Robust Sparse Regression - Detailed Analysis & Overview

Constantine Caramanis (University of Texas at Austin) ... CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 03, 2020 by the ... Po-Ling Loh (University of Wisconsin, Madison) ... Computer Science/Discrete Mathematics Seminar I Topic: Recent advances in This video resumes the main contributions of the paper by [CDKGGS+21] This is a recording of Wojchiech Rejchel's presentation for the statistical learning seminar series on May 29, 2020. Abstract: We ...

Authors: Yongxin Wang (Shandong University), Zhen-Duo Chen (Shandong University), Xin Luo (Shandong University) and Xin- ...

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High Dimensional Robust Sparse Regression

Robust, Interpretable Statistical Models: Sparse Regression with the LASSO

Efficient Algorithms for High Dimensional Robust Learning

A Modern Maximum-Likelihood Theory for High-Dimensional Logistic Regression

Felix Abramovich: High-dimensional classification by sparse logistic regression

Scale Calibration for High-Dimensional Robust Regression

Sparse Regression Comparison

Recent advances in high dimensional robust statistics - Daniel Kane

Outlier Robust Sparse Mean Estimation via Non Convex Optimization

Wojciech Rejchel: Fast and Robust Procedures in High-Dimensional Variable Selection

Preconditioning In Sparse Linear Regression Using Graphical Structure

Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices

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High Dimensional Robust Sparse Regression

High Dimensional Robust Sparse Regression

Constantine Caramanis (University of Texas at Austin) ...

Robust, Interpretable Statistical Models: Sparse Regression with the LASSO

Robust, Interpretable Statistical Models: Sparse Regression with the LASSO

Sparse regression

Efficient Algorithms for High Dimensional Robust Learning

Efficient Algorithms for High Dimensional Robust Learning

This raises the following question: is

A Modern Maximum-Likelihood Theory for High-Dimensional Logistic Regression

A Modern Maximum-Likelihood Theory for High-Dimensional Logistic Regression

Pragya Sur (Stanford University) ...

Felix Abramovich: High-dimensional classification by sparse logistic regression

Felix Abramovich: High-dimensional classification by sparse logistic regression

CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 03, 2020 by the ...

Scale Calibration for High-Dimensional Robust Regression

Scale Calibration for High-Dimensional Robust Regression

Po-Ling Loh (University of Wisconsin, Madison) ...

Sparse Regression Comparison

Sparse Regression Comparison

A comparison between the results of

Recent advances in high dimensional robust statistics - Daniel Kane

Recent advances in high dimensional robust statistics - Daniel Kane

Computer Science/Discrete Mathematics Seminar I Topic: Recent advances in

Outlier Robust Sparse Mean Estimation via Non Convex Optimization

Outlier Robust Sparse Mean Estimation via Non Convex Optimization

This video resumes the main contributions of the paper by [CDKGGS+21] https://arxiv.org/pdf/2109.11515.pdf.

Wojciech Rejchel: Fast and Robust Procedures in High-Dimensional Variable Selection

Wojciech Rejchel: Fast and Robust Procedures in High-Dimensional Variable Selection

This is a recording of Wojchiech Rejchel's presentation for the statistical learning seminar series on May 29, 2020. Abstract: We ...

Preconditioning In Sparse Linear Regression Using Graphical Structure

Preconditioning In Sparse Linear Regression Using Graphical Structure

Frederic Koehler (Stanford) https://simons.berkeley.edu/talks/preconditioning-

Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices

Asymptotic Errors for High-Dimensional Convex Penalized Linear Regression beyond Gaussian Matrices

Asymptotic Errors for

High-Dimensional Sparse Cross-Modal Hashing with Fine-Grained Similarity Embedding

High-Dimensional Sparse Cross-Modal Hashing with Fine-Grained Similarity Embedding

Authors: Yongxin Wang (Shandong University), Zhen-Duo Chen (Shandong University), Xin Luo (Shandong University) and Xin- ...