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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.
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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, …
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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
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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, University of California, Berkeley, CA 94720-3860. Email: [email protected]
@WalmartLabs and University of California, Berkeley The performance of spectral clustering can be considerably improved via regularization, as demonstrated empirically in Amini et al. [ Ann. Statist. 41
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Spectral clustering and the high-dimensional Stochastic Block Model Karl Rohe, Sourav Chatterjee and Bin Yu Department of Statistics University of California Berkeley, CA …
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spectral clustering has many similarities with the nonlinear dimension reduction or manifold learning techniques such as Diffusion maps and Laplacian eigenmaps [Coifman et al. …
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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 …
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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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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
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Feb;71(2 Pt 2):026102. doi: 10.1103/PhysRevE.71.026102. Epub 2005 Feb 4. ... 1 Department of Physics and …
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
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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Departments of Statistics and Electrical Engineering and Computer Sciences ... CA 94720. phone: 510-642-2781 • fax: 510-642-7892 • [email protected]. Welcome. 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 research ...
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 ...
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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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1768 A. JOSEPH AND B. YU Algorithm 1 The RSC-τ Algorithm [2] Input: Laplacian matrix Lτ. Step 1: Compute the n×K eigenvector matrix Vτ. Step 2: Use the K-means algorithm to cluster the rows of Vτ into K clusters. Regularization is introduced in the following way: Let J be a constant matrix with all entries equal to 1/n.Then, in regularized spectral clustering …
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 ...
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