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[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
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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 …
arXiv:0807.3719v1 [stat.ML] 23 Jul 2008 Data Spectroscopy: Eigenspace of Convolution Operators and Clustering Tao Shi∗, Mikhail Belkin† and Bin Yu‡ The Ohio State University∗† and University of California, Berkeley‡ Abstract: This paper focuses on obtaining clustering information in a dis-tribution when iid data are given.
Verma and Meila [17]. A discussion of some limitations of spectral cluster-ing can be found in Nadler and Galun [7]. A theoretical analysis of statis-tical consistency of different types of spectral clustering is provided in von Luxburg, et al [19]. Similarly to spectral clustering methods, Kernel Principal Component
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The Annals of Statistics 2011, Vol. 39, No. 4, 1878–1915 DOI: 10.1214/11-AOS887 © Institute of Mathematical Statistics, 2011 SPECTRAL CLUSTERING AND THE HIGH ...
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Siqi Wu [email protected] Bin Yu [email protected] Department of Statistics University of California Berkeley, CA 94720-1776, USA Editor: Hui Zou Abstract We study the theoretical properties of learning a dictionary from N signals x i 2RK for i= 1;:::;N via ' 1-minimization. We assume that x i's are i:i:d:random linear combina-
Electronic Journal of Statistics Vol. 5 (2011) 935–980 ISSN: 1935-7524 DOI: 10.1214/11-EJS631 High-dimensionalcovarianceestimation byminimizingℓ1-penalized log ...
Departments of Statistics and EECS, University of California at Berkeley, Berkeley, CA 94720, USA. E-mail: [email protected] Reproducibility is imperative for any …
My past work covered research areas in empirical process theory, information theory (MDL), MCMC methods, signal processing, machine learning, high dimensional data inference (e.g. sparse modeling …
[email protected] [email protected] Garvesh Raskutti †Bin Yu,! [email protected] [email protected] Departmentof Statistics†, and Department of Electrical Engineeringand Computer Sciences! University of California, Berkeley Berkeley, CA 94720 November21, 2008 Abstract
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,
from data, interpreted in a broad sense. Statistics as a discipline has its primary role as assisting this knowledge/information acquisition process in a principled and scienti c manner. IT data are massive or high-dimensional, no matter whether the forms are old (numeric) or new (text, images, videos, sound, and multi-media).
Electronic Journal of Statistics Vol. 5 (2011) 935–980 ISSN: 1935-7524 DOI: 10.1214/11-EJS631 High-dimensionalcovarianceestimation byminimizingℓ1-penalized log ...
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
spectral clustering, this provides insight into a graph visualization technique. Our method of studying the eigenvectors of random matrices is original. 1. Introduction. Researchers in …
Bin Yu is the Class of 1936 Second Chair in the College of Letters and Science and a professor in the Department of Statistics. Her research interests are varied and included empirical processes, Markov Chain …
The Annals of Statistics 2009, Vol. 37, No. 6B, 3960–3984 DOI: 10.1214/09-AOS700 c Institute of Mathematical Statistics, 2009 DATA SPECTROSCOPY: EIGENSPACES OF CONVOLUTION OPERATORS AND CLUSTERING By Tao Shi1, Mikhail Belkin2 and Bin Yu3 Ohio State University, Ohio State University and University of California, Berkeley
four spectral channels. Cloud detection is particularly di–cult in the snow- and ice-covered po- ... [email protected] yDepartment of Meteorology, The Pennsylvania State University, University Park, PA 16802. Email: [email protected] zJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109-8099. Email:
corresponds to the usual spectral clustering algorithm. Our theoretical results assume that the data is randomly generated from a stochastic block model (SBM), which we review in …
Amongst the 36 spectral radiances available on the Moderate Resolution Imag-ing Spectroradiometer (MODIS) seven of them are used operationally for detection of …
Berkeley, CA 94720 [email protected] Sophie Clavier Dept. of International Relations San Francisco State University San Francisco, CA 94132 [email protected] ABSTRACT We analyze the image" of a given query word in a given corpus of text news by producing a short list of other words
Amongst the 36 spectral radiances available on the Moderate Resolution Imag-ing Spectroradiometer (MODIS) seven of them are used operationally for detection of ... ∗Department of Statistics, The Ohio State University, Columbus, OH 43210-1247. Email: ... University of California, Berkeley, CA 94720-3860. Email: [email protected]
partment of Statistics∗ at University of California, Berkeley ... @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 …
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-work for estimating mixture distributions, specifically Gaussian mixture models. In physics, spectroscopy is often used for the
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Journal of Machine Learning Research 18 (2018) 1-56 Submitted 3/16; Revised 7/17; Published 4/18 Local Identi ability of ' 1-minimization Dictionary Learning: a Su cient and Alm
I'm Bin Yu, the head of the Yu Group at Berkeley, which consists of 15-20 students and postdocs from S tatistics and EECS. I was formally trained as a statistician, but my …
Statistics at UC Berkeley. We are a community engaged in research and education in probability and statistics. In addition to developing fundamental theory and methodology, we are actively involved in …
Research Description. Bin Yu is the Class of 1936 Second Chair in the College of Letters and Science and a professor in the Department of Statistics. Her research interests are varied and included empirical processes, Markov Chain Monte Carlo methods, information theory and signal processing. She is currently working on statistical machine ...
d Department of Statistics, University of California, Berkeley, CA 94720-3860, United States ABSTRACT Detection of clouds in satellite-generated radiance images, including those from MODIS, is an important first step in many applications of these data. In this paper we apply spectral unmixing to this problem with the aim of estimating
nologies must be integrated into statistics, and statistical thinking must be integrated into computer technologies or into the making of the cyberinfrastructure. 1 Introduction Information technology (IT) is a broad subject concerned with technology and other aspects of managing and processing information, especially in large organizations.
The performance of spectral clustering can be considerably improved via regularization, as demonstrated empirically in Amini et al. [2]. Here, we provide an attempt at quantifying …
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 …
CA 94720 (Email: [email protected]). Eugene Clothiaux is Associate Professor, Department of Mete-orology, Pennsylvania State University, University Park, PA 16802 (Email: [email protected]). Amy Braver- ... in four spectral bands (blue, green, red, and near-infrared). The view zenith angles of the nine
Spectral clustering is a popular and computationally feasible method to discover these communities. The Stochastic Block Model (Holland et al., 1983) is a social network …
