Research affiliations and useful links
Designated Emphasis in
Communication, Computation and Statistics: An interdisciplinary
program that bridges the Department of Statistics and the Department
of Electrical Engineering and Computer Sciences.
Statistical Machine Learning: A group of researchers and students
from EECS and Statistics.
A communications and signal processing group which is housed in
the Wong Center in the EECS Department.
Some seminars and reading groups
Upcoming seminars in the Department of Statistics.
Networking and Communication Seminar in the Department of EECS.
Graphical models and machine learning
Statistics and privacy
Distributed algorithms and optimization
T. Hastie, R. Tibshirani and M. J. Wainwright (2015).
Statistical Learning with Sparsity: the Lasso and Generalizations.
Chapman and Hall/CRC Press, Series in Statistics and Applied Probability.
M. J. Wainwright and M. I. Jordan (2008).
Graphical models, exponential families, and variational inference.
Foundations and Trends in Machine Learning, Vol. 1, Numbers 1--2, pp. 1--305,
Graphical models and message-passing
Statistics and privacy
Optimization and distributed algorithms
Coding, data compression, algorithms
Statistical image processing
Statistical approaches to biological vision
Tutorial Materials on High-Dimensional Statistics:
Slides from lectures (PDF)
Statistical Science Paper (PDF)
Tutorial Materials on Graphical Models, Variational Methods and Message-Passing
Machine Learning Summer School, Kyoto, Japan. September 2012
Slides (Part I) Basics, max-product and LP relaxation
Slides (Part II) Sum-product, variational formulation
Slides (Part III) Learning graphical models from data
Rough lecture notes: On factorization, Markov properties, Hammersley-Clifford, message-passing algorithms, junction tree, and basic aspects of graphical
Wainwright and Jordan monograph: More advanced material on exponential
families, duality, and variational methods.
Tutorial Lectures on Linear Programming Decoding and Conic Relaxations:
Alekh Agarwal Research Scientist, Microsoft Research, New York.
Assistant Professor, Dept. of Statistics, UCLA
Joseph Bradley Databricks
Alexandros D.G. Dimakis
Associate Professor, Department of ECE, UT Austin
John Duchi, Assistant
Professor, Departments of Statistics and EE, Stanford University
Pamela Lee, Associate, Gibson, Dunn & Crutcher
Assistant Professor, Department of Statistics, Univ. Pennsylvania
Matt Johnson, Postdoc, Harvard University
Johannes Lederer, Assistant Visiting Professor, Cornell University
Assistant Professor, Department of Statistics, Yale University.
Associate Professor, Department of Statistics, Univ. Michigan
Nima Noorshams, Qualcomm Research
Group leader, Max Planck Institute, Tuebingen
Assistant Professor, Department of Statistics, Univ. Wisconsin-Madison
Assistant Professor, Department of CS, UT Austin
Assistant Professor, Department of ECE, University of Hawaii
Sameer Vermani, Engineer, Qualcomm
Last updated 09/2014