Electronic Journal of Statistics Vol. 5 (2011) 935–980 ISSN: 1935-7524 DOI: 10.1214/11-EJS631 High-dimensionalcovarianceestimation byminimizingℓ1-penalized log ...
Statistics at UC Berkeley | Department of Statistics
Subject: Image Created Date: 6/20/2008 11:36:43 AM
Group Member: Peng Zhao
Professor University of California Department of Statistics 367 Evans Hall #3860 Berkeley CA 94720-3860 phone: 510-642-2021 email: [email protected] homepage: …
Stability
robust statistics in high-dimensional regression models. In other words, we tell an interwinding story of scientific investigation and statistical developments. The rest of the …
High-dimensionalcovarianceestimation byminimizing ℓ …
Berkeley, CA 94720-1776 USA e-mail: [email protected] [email protected] [email protected] [email protected] Abstract: Given i.i.d. observations of a random vector X ∈ Rp, we study the problem of estimating both its covariance matrix Σ∗, and its inverse covariance or concentration …
Statistics at UC Berkeley | Department of Statistics
Learn how to use the L1 norm for robust estimation and sparse recovery in this paper by Aenlle-Rocha and Yu, two professors from Berkeley's statistics department.
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Statistics at UC Berkeley | Department of Statistics
Spectral clustering and the high-dimensional Stochastic Block Model Karl Rohe, Sourav Chatterjee and Bin Yu Department of Statistics University of California Berkeley, CA …
University of California, Berkeley
Created Date: 11/3/2003 6:21:01 PM
Bin Yu | EECS at UC Berkeley
Bin Yu is Chancellor's Professor in the Departments of Statistics and of Electrical Engineering & Computer Sciences at the University of California at Berkeley. Her …
High-dimensionalcovarianceestimation byminimizing ℓ
Berkeley, CA 94720-1776 USA e-mail: [email protected] [email protected] [email protected] [email protected] Abstract: Given i.i.d. observations of a random vector X ∈ Rp, we study the problem of estimating both its covariance matrix Σ∗, and its inverse covariance or concentration …
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A Hierarchical Bayesian Approach for Aerosol …
89 particles in the atmosphere justify the spatial smoothness of AOD from a physical viewpoint. To flexibly 90 describe various aerosol conditions, our model regards AOD values and mixing vectors as continuous pa- 91 rameters. This expands the set of possible compositions beyond the 74 pre-fixed choices of MISR. We show 92 how this enriched …
Group Member: Peng Zhao
Group Member: Peng Zhao. Bin Yu. Professor. University of California. Department of Statistics. 367 Evans Hall #3860. Berkeley CA 94720-3860. phone: 510-642-2021.
University of California, Berkeley
Created Date: 2/16/2010 1:33:21 PM
Spectral clustering and the high-dimensional stochastic …
spectral clustering has many similarities with the nonlinear dimension reduction or manifold learning techniques such as Diffusion maps and Laplacian eigenmaps [Coifman et al. (2005), Belkin and Niyogi (2003)]. The normalized graph Laplacian L is an essential part of spectral clustering, Diffusion maps and Laplacian eigenmaps.
Cloud Detection over Snow and Ice Using MISR Data
four spectral channels. Cloud detection is particularly di–cult in the snow- and ice-covered po-lar regions and availability of the novel MISR angle-dependent radiances motivates the current study on cloud detection using statistical methods. Three schemes using MISR data for polar cloud detection are investigated in this study.
stat.berkeley.edu
stat.berkeley.edu
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Bin Yu | EECS at UC Berkeley
Biography. Bin Yu is Chancellor's Professor in the Departments of Statistics and of Electrical Engineering & Computer Sciences at the University of California at Berkeley. Her current research interests focus on statistics and machine learning theory, methodologies, and algorithms for solving high-dimensional data problems.
Research
Current research topics of my group cover sparse modeling (e.g. Lasso), structured sparsity (e.g. hierarchical and group and graph path), analysis and methods for spectral clustering for undirected and directed graphs; and our data problems come from diverse interdisciplinary areas including genomics, neuroscience, remote sensing, document ...
Retrieval Using MISR Data A Hierarchical Bayesian …
Yueqing Wang, Department of Statistics, University of California at Berke-ley, CA 94720-3860 (E-mail: [email protected]). Xin Jiang, LMAM, School of Mathematical Sciences, Peking University, Beijing 100871, China. Bin Yu, Department of Electrical Engineering and Computer Sciences, Uni-versity of California at Berkeley, CA 94720-3860.
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Veridical data science INAUGURAL ARTICLE
Contributed by Bin Yu, November 25, 2019 (sent for review January 25, 2019; reviewed by Jun S. Liu, David Madigan, and Larry Wasserman) Building and expanding on principles …
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Contribute to lqdid/id development by creating an account on GitHub.
Bin Yu
Research. In 2014, I was elected to the National Academy of Sciences based on my statistical and scientific contributions, as well as my broad vision of data science best described in my article Veridical Data Science, written together with my former student Karl Kumbier. In this work, I introduced a framework based on three principles ...
University of California, Berkeley
University of California, Berkeley
Bin Yu | Department of Statistics
[email protected]. Dissertation. Some Results on Empirical Processes and Stochastic Complexity. Dissertation Advisor. Terence Speed, Lucien LeCam. Program. ... Department of Statistics 367 Evans Hall, University of California Berkeley, CA 94720-3860 T 510-642-2781 | F 510-642-7892
Bin Yu
Welcome I'm Bin Yu, the head of the Yu Group at Berkeley, which consists of 15-20 students and postdocs from Statistics and EECS. I was formally trained as a statistician, …
Bin Yu | Department of Statistics
Current Website https://binyu.stat.berkeley.edu Office / Location 409 Evans Hall Phone (510) 642-2021 Email [email protected] Research Expertise and Interests statistical inference for high …
Statistics at UC Berkeley | Department of Statistics
Statistics at UC Berkeley | Department of Statistics