Good words from the NY Times:
"For Today's Graduate, Just One Word: Statistics" here .
"Advertising Companies Fret Over a Digital Talent Gap" here .
"What Are the odds That Stats Would Be This Popular?" here .
"What You (Really) Need to Know" here .
And from Science
"Why Statistics" here
"Statistical Insights are Crucial" here .
Bin Yu on Data Science here .
Statistics 860 Estimation of Functions From Data (aka Statistical Machine Learning) will be given in the fall. Course description here. Stat 709 NOT required.
Link to Conference on Nonparametric Statistics for Big Data here.
Link to Madison faculty with Machine Learning Interests here.
IJ Schoenberg-Hilldale Professor of Statistics,
Professor of Biostatistics and Medical Informatics,
and Professor of Computer Sciences (by courtesy).
Department of Statistics
University of Wisconsin-Madison
Medical Science Center
1300 University Ave
Madison, WI 53706 USA
Fax: (608) 262-0032
e-mail wahba "at" stat.wisc.edu (replace "at" with the "at" symbol).
Coded email from people I dont know may not be read, plaintext please.
Wisconsin Senior Olympics 2013 medalist smiles summer winter photos David Callan
TR LIST: Click here for Tech Reports and mss
SOFTWARE: Links to **LPS Algorithm****new**, RKPACK, GRKPACK, GCVPACK, NETLIB/GCV, R.
TALKS: Directory for talk abstracts, references and some overheads.
BOOK: "Spline Models for Observational Data" is in the SIAM e-books library. If you have a University of Wisconsin-Madison ID you can find it here
PhD STUDENTS Prospective, In Progress and Former PhD students
PUBLICATIONS PubList, SearchLinks to MathRev and Zentralblatt ..
Keywords for research: risk factor estimation; variational data assimilation; climate data analysis; demographic data analysis; ill-posed inverse problems; variational methods; adaptive tuning; smoothing spline ANOVA; bias-variance tradeoff; generalized cross-validation; reproducing kernel Hilbert space methods; supervised machine learning; radial basis functions; support vector machines; numerical methods for large data sets; dissimilarity information.