statweb.stanford.edu
Brad Efron's Site
http://statweb.stanford.edu/~ckirby/brad
Professor of Statistics and Biomedical Data Science. A new book by Bradley Efron and Trevor Hastie. The text proceeds in three parts, with each succeeding era building on the successes of its predecessor: Part I. Of the book reviews classical inference, Bayesian, frequentist, and Fisherian. Part II. Concerns early computer-age developments, from the mid 1950s to the 1990s: empirical Bayes, generalized linear models, cross-validation and C p, the jackknife and bootstrap, and many others.
cs.stanford.edu
Percy Liang
http://cs.stanford.edu/~pliang
Assistant Professor of Computer Science. Natural Language Processing Group. 112;liang@cs.stanford.edu. I am co-organizing three NIPS 2016 workshops: Reliable Machine Learning in the Wild. Nonconvex Optimization for Machine Learning: Theory and Practice. And Deep Learning for Action and Interaction. Regarding (i), think of a sentence (e.g., "What fraction of CO2 emissions is from the top 5 countries? As encoding a computer program. XRDS magazine), a more general tutorial on natural language understanding.
jamesjohndrow.com
James Johndrow › Home
http://jamesjohndrow.com/www.datapad.io
Jj (at) stat (dot) duke (dot) edu. Latest updates: I successfully defended my Ph.D. dissertation in January, and starting in September I will be a Stein fellow in the Statistics Department at Stanford. I am a Ph.D. candidate in the Department of Statistical Science. At Duke and an alum of Amherst College. My CV is available for download here. See my publications page. For a list of publications with links. My research program has two main components:. A few specific threads include. A leading quantitativ...
