Abstract: Compressed sensing or compressive sampling (CS) is a powerful technique to represent signals at a sub-Nyquist sampling rate while retaining the capacity of perfect (or near perfect) reconstruction of the signal, provided the signal is kn
Abstract: Concurrent software is everywhere. Ensuring reliability of concurrent software is a daunting task. In this talk, I will present the basics of verification, what is so hard about concurrency, and recent efforts to tame the problem.
Abstract: There seems to be a general consensus among mathematicians about the notion of a correct proof. Still, in mathematical literature, many invalid proofs remain accepted over a long period of time.
Abstract: Sparse Recovery refers to a broad collection of techniques that aim to exploit sparsity to dramatically reduce the "cost" of reconstructing a low dimensional "sparse" dataset embedded in a prohibitively high dimensional space.
Abstract: Algorithmic game theory is an active and impactful area of research that in recent years has found many applications in the study of large strategic environments, like online markets and auctions, as well as social and biological systems
Abstract: In this talk a duality relation between the Mane's potential and Mather's action functional is derived in the context of convex and state-dependent Hamiltonians.
