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 ...
Biography. Bin Yu is Chancellor's Distinguished Professor and Class of 1936 Second Chair in the Departments of statistics and EECS, and Center for Computational Biology at UC Berkeley. She obtained her BS Degree in Mathematics from Peking University, and MS and PhD Degrees in Statistics from UC Berkeley. She was Assistant Professor at UW ...
Statistics at UC Berkeley | Department of Statistics
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 …
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.
{peter.sollich,zoran.cvetkovic}@kcl.ac.uk, [email protected]). Finan-cial support from EPSRC under grant EP/D053005/1 is gratefully acknowl-edged. Bin Yu thanks the National Science Foundation for grants NSF SES-0835531 (CDI) and NSFC (60628102). aim to reduce explicitly the effects of noise on spectral
1 A Hierarchical Bayesian Approach 2 for Aerosol Retrieval Using MISR Data Yueqing Wang 1;, Xin Jiang 2; y, Bin Yu 1;3, Ming Jiang 2;4 3 1 Department of Statistics, University of California at Berkeley, CA 94720-3860, U.S. 4 2 LMAM, School of Mathematical Sciences, Peking University, Beijing 100871, China. 5 3 Department of Electrical …
Department of Statistics. 367 Evans Hall #3860. Berkeley CA 94720-3860. phone: 510-642-2021. email: [email protected]. homepage: …
Current Website https://binyu.stat.berkeley.edu Office / Location 409 Evans Hall Phone (510) 642-2021 Email [email protected] Research Expertise and Interests …
stat berkeley edu binyupsspectral 791 pdf google search. stat berkeley edu binyu ps spectral zenith 791 pdf google, stat berkeley edu_ binyu_ps_spectral SBM 791 Molinos utech modelo kt 120bmj stat berkeley edu_ Get Quote. Visio P …
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 …
Tao Shi [email protected] Department of Statistics, Ohio State University Mikhail Belkin [email protected] Department of Computer Science and Engineering, Ohio State University Bin Yu [email protected] Department of Statistics, University of California Berkeley Abstract In this paper we develop a spectral frame-
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The area of high-dimensional statistics deals with estimation in the "large p, small n" setting, where p and n corre-spond, respectively, to the dimensionality of the data and the sample size. Such high-dimensionalproblems arise in a variety of applications, among them remote sensing, computational biology and natural language processing, where
Tao Shi is Assistant Professor, Department of Statistics, the Ohio State University, Columbus, OH 43210 (Email: [email protected]). Bin Yu is Professor, Department of Statistics, University of California, Berkeley, CA 94720 (Email: [email protected]). Eugene Clothiaux is Associate Professor, Department of Mete-
Department of Statistics University of California at Berkeley Berkeley, CA 94720-3860 USA Email: [email protected] Abstract—The paper is focused on the problem of discrete universal denoising: one estimates the input sequence to a discrete channel based on the observation of the entire output
Bin Yu - Research 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 …
Spectral clustering and the high-dimensional Stochastic Block Model Karl Rohe, Sourav Chatterjee and Bin Yu Department of Statistics University of California Berkeley, CA …
[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
Electronic Journal of Statistics Vol. 5 (2011) 935–980 ISSN: 1935-7524 DOI: 10.1214/11-EJS631 High-dimensionalcovarianceestimation byminimizingℓ1-penalized log ...
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 …
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.
The field of statistics indeed has been undergoing major changes over the last few decades. There has been consider-able discussion and introspection within the statistics commu-nity regarding the challenges and the future of the discipline (see, e.g., Lindsay, Kettenring, and Siegmund 2004). In this ar-
In order to study spectral clustering under the Stochastic Block Model, we first show that under the more general latent space model, the eigenvectors of the …
This is a research paper by Bin Yu, a professor of statistics and electrical engineering at UC Berkeley, on the topic of network tomography. The paper introduces the basic concepts and methods of network tomography, which is the study of the internal structure and performance of a network based on end-to-end measurements. The paper also reviews …
spectral clustering has many similarities with the nonlinear dimension reduction or manifold learning techniques such as Diffusion maps and Laplacian eigenmaps [Coifman et al. …
ulate more exchanges in the statistics community as well as among the different disciplines so that statistics as a field adequately positions itself in the future development of cyberin-frastructure. The rest of the paper is organized as follows. Section 2 describes three areas of science where massive data sets arise.
The area of high-dimensional statistics deals with estimation in the "large p, small n" setting, where p and n corre-spond, respectively, to the dimensionality of the data and the sample size. Such high-dimensionalproblems arise in a variety of applications, among them remote sensing, computational biology and natural language processing, where
Amongst the 36 spectral radiances available on the Moderate Resolution Imag-ing Spectroradiometer (MODIS) seven of them are used operationally for detection of ... [email protected] ... ‡Department of Statistics, University of California, Berkeley, CA 94720-3860. Email: [email protected]
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.
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, but my research interests and achievements extend beyond the realm of statistics. Together with my group, my work has leveraged new computational developments to solve ...
closely related to non-parametric spectral methods, such as spectral clustering (e.g., [8]) and Kernel Prin-cipal Components Analysis [11]. Those methods, as well as certain methods in manifold learning (e.g., [1]), construct a kernel matrix or a graph Laplacian ma-trix associated to a data set. The eigenvectors and
telephone numbers, are just few examples of searches on Google. Web search is the hottest topic in IR, but its scale is gigantic and desires a huge amount of computation. First, the target of web search is moving: the content of a website is changing within a week for 30% or 40% of the websites (Fetterly et al, 2004 [15]).
Departments of Statistics and Electrical Engineering and Computer Sciences ... 367 Evans Hall #3860 • Berkeley, CA 94720. phone: 510-642-2781 • fax: 510-642-7892 • [email protected]. Welcome. I'm Bin Yu, the head of the Yu Group at ... UC Berkeley to lead $10M NSF/Simons Foundation program to investigate theoretical underpinnings …
compare SPORE algorithms to state-of-the-art sparse regression algorithms, and show that SPORE methods, motivated by real applications, outperform the other methods in terms of both interpretability and prediction accuracy. 1 Introduction Computing systems today are ubiquitous, and range from the very small (e.g., iPods, cellphones,
statistics, semiparametric statistics, and Bayesian sensitivity anal-ysis (ref. 15 and references therein). These methods have been enabled in practice through computational advances and allow researchers to investigate the reproducibility of data results. Econometric models with partial identification (ref. 16 and ref-
