Graduate Student and Postdoc in ECE respectively.
Nikhil’s Abstract —————————— In applications ranging from communications and image processing to genetics, signals can be modeled as lying in a union of subspaces. Under this model, signal coefficients that lie in certain subspaces are active or inactive together. The potential subspaces are known in advance, but the particular set …
Title: Canonical Estimation in a Rare-Events Regime by Vincent Tan Abstract: We propose a general methodology for performing statistical inference within a `rare-events regime’ that was recently suggested by Wagner, Viswanath and Kulkarni. Our approach allows one to easily establish consistent estimators for a very large class of canonical estimation …
Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees. However, in linear inverse problems such as deconvolution, tomography, and compressed sensing, the presence of a sensing or observation matrix leads to reconstruction problems that are intractable or non-convex optimizations. Past work has dealt …