Sekhar Tatikonda

Sekhar Tatikonda's picture
Associate Professor of Statistics and Data Science and of Electrical Engineering
Address: 
17 Hillhouse Ave, New Haven, CT 06511
(203) 432-4714

Courses

STAT 667/ENAS503/AMTH605 Probabilistic Networks, Algorithms, and Applications

This course examines probabilistic and computational methods for the statistical modeling of complex data. The emphasis is on the unifying framework provided by graphical models, a formalism that merges aspects of graph theory and probability theory. Graphical models: Markov random fields, Bayesian networks, and factor graphs. Algorithms: filtering, smoothing, belief-propagation, sum-product, and junction tree. Variational techniques: mean-field and convex relaxations. Markov processes on graphs: MCMC, factored HMMs, and Glauber dynamics. Some statistical physics techniques: cavity and replica methods. Applications to error-correcting codes, computer vision, bio-informatics, and combinatorial optimization.

Term: Fall
Day/Time: Tuesday & Thursday, 1:00-2:15

STAT 699ab Research Seminar in Probability

Continuation of the Yale Probability Group Seminar. Student and faculty explanations of current research in areas such as random graph theory, spectral graph theory, Markov chains on graphs, and the objective method.

Credit only with the explicit permission of the seminar organizers.

http://www.stat.yale.edu/~ypng/

Term: Spring
Day/Time: Friday 11:00pm - 1:00pm

STAT 699ab Research Seminar in Probability

Continuation of the Yale Probability Group Seminar. Student and faculty explanations of current research in areas such as random graph theory, spectral graph theory, Markov chains on graphs, and the objective method.

Credit only with the explicit permission of the seminar organizers.

http://www.stat.yale.edu/~ypng/

Term: Fall
Day/Time: Friday 11:00pm - 1:00pm