Data Science Seminar
Date: November 10th
Time: 8:30 pm to 9:30 pm
CVXR: Disciplined Convex Programming in R
Senior research scientist, Department of Biomedical Data Science and Department of Statistics, Stanford University, USA.
Convex optimization plays an important role in statistics and machine learning. Therefore tools for specifying and solving convex problems in a routine fashion are very useful. Disciplined convex programming (DCP) is a convention for formulating convex problems by combining constants constants, variables, and parameters using a library of functions with known curvature and monotonicity properties. This allows one to specify problems in a natural mathematical syntax rather than the restrictive standard form required by most solvers. In this talk I will introduce CVXR, a package that implements DCP in the widely used language R and demonstrate CVXR's modeling framework with several applications. This is joint work with Anqi Fu and Stephen Boyd.
About the speaker: Balasubramanian Narasimhan ("Naras" to colleagues) studied at the what is now the National Public School in Chennai. He did his B.Sc. in Maths at Loyola College, Chennai and his M.Sc. in Applied Mathematics at PSG College of Technology, Coimbatore. He got his Ph.D. from Florida State University, advised by George Marsaglia. He was an Assistant Professor at University of Minnesota and Penn State University before moving to Stanford in 1996 where he is a Senior Research Scientist in the Department of Statistics and in the Department of Biomedical Data Sciences. He is also the Director of the Data Coordinating Center in the Stanford School of Medicine. His research interests are in optimization, statistical computing, machine learning, and clinical trial design.