Bin Yu. Professor, Department of Statistics. Over the past 30 years, UC Berkeley statistics Professor Bin Yu has covered a lot of territory, both in her research field and in sharing …

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Veridical data science extracts reliable and reproducible information from data, with an enriched technical language to communicate and evaluate empirical evidence in the context of human decisions and domain knowledge. Building and expanding on principles of statistics, machine learning, and the sciences, Yu and Kumbier (PNAS, …

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, USA e-mail: [email protected] [email protected] [email protected] Abstract: Networks or graphs can easily represent a diverse …

2000. The minimum description length principle in coding and modeling. A Barron, J Rissanen, B Yu. IEEE transactions on information theory 44 (6), 2743-2760., 1998. 1422. 1998. Definitions, methods, and applications in interpretable machine learning. WJ Murdoch, C Singh, K Kumbier, R Abbasi-Asl, B Yu.

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

In this work, I introduced a framework based on three principles: predictability, computability and stability (abbreviated to PCS). This framework helps guide practitioners who 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

Bin Yu. Chancellor's Distinguished Professor for Statistics, Electrical Engineering and Computer Science. Class of 1936 Second Chair. Email: [email protected]. Lab …

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.

Bin Yu. Chancellor's Distinguished Professor for Statistics, Electrical Engineering and Computer Science. Class of 1936 Second Chair. Email: [email protected]. Lab Webpage. Bin Yu's research groups finds new computational developments to solve important scientific problems by combining novel statistical machine learning approaches ...

fitted distribution is quite clear, occurring at a value of 0.215 and falling in the expected range from. 0.08 to 0.40, and the threshold from the previous visit is not needed. Using thresholdCORR = 0.75, thresholdSD = 2.0, and thresholdNDAI = 0.215 to classify the pixels in the data unit, we obtain a.

Bin Yu is the Class of 1936 Second Chair in the College of Letters and Science and a Chancellor's distinguished professor in the Department of Statistics, EECS and Center for Computational Biology. She is also a senior advisor at the Simons Institute for Theory of Computing. Her current research has focused on the practice and theory of machine ...

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tion g is given byDg(A B) := log det. + log det B + B 1, A B, (7)valid for any A, B p+ that are strictly positive definite. This divergence suggests a natural way to estimate concen-tration matrices—n. e divergence S Dg( ) —or equivalently, by minimizing the functionmin, log det, (8)0where we have discarded terms independent of, and ...

Bin Yu. After enduring 10 years of social upheaval, including the death of her father at the hands of the Red Guard, as a young living through Mao Tse Tung's Cultural …

Veridical data science. Bin Yua,b,c,d,1 and Karl Kumbiera. ems Biology Division, Berkeley, CA 94720This contribution is part of the special series of Inaugural Articles by members of the Nati. Liu, David Madigan, and Larry Wasserman)Building and expanding on principles of statistics, machine learn-ing, and scientific inquiry, we propose the ...

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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-

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, and serves as a senior advisor at the Simons Institute for the Theory of Computing, all at UC Berkeley. She obtained her BS Degree in Mathematics from Peking University, and MS ...

1. Introduction. Data clustering based on eigenvectors of a proximity/affinity matrix (or its normalized version) has become popular in machine learning, computer vision and other areas. Given data x1,, xn ∈ Rd, this family of algorithms construct. n×n affinity matrix (Kn)ij = K(xi, xj)/n based on a kernel function, such as.

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-work for …

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Stability. BIN YU. Departments of Statistics and EECS, University of California at Berkeley, Berkeley, CA 94720, USA. E-mail: [email protected]. Reproducibility is imperative for any scientific discovery. More often than not, modern scientific findings rely on statistical analysis of high-dimensional data.

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 …

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 …

Cloud Detection over Snow and Ice Using MISR Data. Clouds play a major role in Earth's climate and cloud detection is a crucial step in the processing of satellite observations in …

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]).

The view zenith angles of the nine cameras are 70.5 (Df), 60 (Cf), 45.6 (Bf), and 26.1 (Af) in the forward direction, 0.0 (An) in the nadir direction and 26.1 (Aa), 45.6 (Ba), 60 (Ca) …