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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. …

Spectral clustering and the high-dimensional Stochastic Block Model Karl Rohe, Sourav Chatterjee and Bin Yu Department of Statistics University of California Berkeley, CA 94720, U

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 …

[Breiman (2001)] is a must-read in my graduate applied statistics class at Berkeley. And I am inspired every time when I think of Leo's creativity, originality, and humanity. REFERENCES Buhlmann, P.and Yu, B.(2003). Boosting with the L2 loss: Regression and classification. ... E-mail: [email protected]. Created Date: 7/18/2012 6:09:27 ...

In this course we will illustrate how the basic questions and tools of Information Theory relate to statistical practice and theory. Tentative Schedule. First Week (8/30,9/1): Introduction. History on entropy. Overview of the course. Code. Decoding. Examples of real codes. Reading: C. Shannon (1948).

[email protected] Abstract: Networks or graphs can easily represent a diverse set of data sources that are characterized by interacting units or actors. Social networks, representing people ... Spectral clustering is a popular and computationally feasible method to discover these communities. The Stochastic Block Model (Holland et al ...

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In this talk, I would like to cover both theory and pratcice of L1 penalized minimization. First, I will give a brief overview of recent theoretical results on model selection consistency (when p>>n) of Lasso and graphical Lasso. Second, I will present on-going collaborative research with the Gallant Lab at Berkeley on understanding visual pathway.

[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

Department of Statistics. Department of Electrical Engineering & Computer Science. University of California, Berkeley. Chan-Zuckerberg Biohub Investigator. mail: 367 Evans Hall #3860 • Berkeley, CA 94720 • phone: …

2020 Fall Statistical Models: Theory and Application [STAT 215A] 2019 Fall Statistical Models: Theory and Application [STAT 215A] 2019 Spring Modern Statistical Prediction and Machine Learning [STAT 154]

Research Expertise and Interest. machine learning, trustworthy data science and AI, interdisciplinary research in biomedicine, neuroscience, and climate science.. Research Description. Bin Yu is the Class of 1936 …

Berkeley, CA 94720-3860 | stark [at] stat.berkeley.edu | 510-394-5077 | @philipbstark. My research centers on inference problems and uncertainty quantification, especially confidence procedures tailored for specific goals. I've published on causal inference, the U.S. Census, climate, clinical trials, cosmology, earthquake prediction and …

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.

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Benson Au's Home Page. Benson Au. E-mail address:Office: 313 Evans Hall. Postal Address: Department of Statistics. University of California, Berkeley. 367 Evans Hall # 3860. Berkeley, CA 94720-3860.

the spectral channels necessary for global cloud detection. Amongst the 36 spectral channels available on the MODIS sensor seven of them were chosen for detection of clouds in daytime polar regions (Ackerman et al., 1998). To illustrate the information content within the seven spectral radiances of MODIS used

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.

The undergraduate major at Berkeley provides a systematic and thorough grounding in applied and theoretical statistics as well as probability. The quality and dedication of the teaching staff and faculty are extremely high. A major in Statistics from Berkeley is an excellent preparation for a career in science or industry, or for further ...

Preface, "An introduction to Air Navigation" (1943) by H. C. Carver, published by Edwards Brothers, Inc. Carver: early "machine learner". Air navigation is the process of planning, recording, and controlling the movement of a craft from one place to another. Carver got the first Hollerith tabulating machine at U-M (later IBM).

E-mail: [email protected] Reproducibility is imperative for any Current Website https://binyu.stat.berkeley.edu Office / Location 409 Evans Hall Phone (510) 642-2021 Email [email protected] Research Expertise and Interests Bin Yu Department of Statistics

In this paper an MKL-based unmixing algorithm is proposed for MODIS pixel cloud fraction estimation. In estimating pixel cloud fraction this algorithm goes beyond existing, operational ones. Algorithm parameters are set using training data obtained from the variable CloudFraction in the CALIPSO/CloudSat product that is collocated with.

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 …

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; …

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-

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