Sketching for M-Estimators: A Unified Approach to Robust Regression

preview_player
Показать описание
David Woodruff, IBM Almaden
Information Theory, Learning and Big Data
  1. Simons Institute
  2. Simons Institute
  3. UC Berkeley
  4. computer science
  5. theory of computing
  6. Information Theory
Рекомендации по теме
Sketching for M-Estimators: 0:27:39

Sketching for M-Estimators: A Unified Approach to Robust Regression

MATH3714, Section 18.1: 0:12:01

MATH3714, Section 18.1: M-Estimators

Lecture 8: Inference 1:05:11

Lecture 8: Inference with M-Estimators

26 Robust Regression 0:25:19

26 Robust Regression Techniques

Lecture 7: Asymptotic 0:55:27

Lecture 7: Asymptotic Properties of M-Estimators

Lecture56 (Data2Decision) Robust 0:21:52

Lecture56 (Data2Decision) Robust Regression

Consistency and normality 0:17:41

Consistency and normality of M-estimators: Part 1

'M-estimators of scatter 0:16:47

'M-estimators of scatter with eigenvalue shrinkage' by Prof. Esa Ollila

Lecture55 (Data2Decision) Robust 0:20:43

Lecture55 (Data2Decision) Robust Estimation

technical view on 0:00:37

technical view on M-estimator performance during extreme secondaray motion

Multigrain: a unified 0:50:00

Multigrain: a unified image embedding for classes (...) - Thirion - Workshop 3 - CEB T1 2019

Sketching as a 1:02:44

Sketching as a Tool for Numerical Linear Algebra

Calculating M-Estimators for 0:07:26

Calculating M-Estimators for Regression Models using SPSS

Andreas Andresen. Finite 0:38:45

Andreas Andresen. Finite sample analysis of semiparametric M-Estimators

Lecture57 (Data2Decision) Robust 0:10:51

Lecture57 (Data2Decision) Robust Regression in R

Robust Sparse Covariance 0:48:13

Robust Sparse Covariance Estimation by Thresholding Tyler's M-estimator

Rigorous Guarantees for 0:13:55

Rigorous Guarantees for Tyler's M-Estimator via Quantum Expansion

Designing Robust Learners 0:53:22

Designing Robust Learners

Samson Zhou: Tight 0:56:47

Samson Zhou: Tight Bounds for Adversarially Robust Streams and Sliding Windows

Robust regression 0:11:52

Robust regression

POLS 506: Bayesian 1:51:18

POLS 506: Bayesian and Nonparametric Statistics - Lecture 1: Model Assessment and Validation

Outlier detection - 0:25:54

Outlier detection - Robust regression techniques

Lecture 21 - 0:45:33

Lecture 21 - Density Estimation - Part I - 2019

Sketching for Linear 1:09:35

Sketching for Linear Algebra: Basics of Dimensionality Reduction and CountSketch II