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Since 1984 there has been a concentrated effort to develop efficient interior-point methods for linear programming (LP). In the last few years researchers have begun to appreciate a very important pro...
In a second-order cone program (SOCP) a linear function is minimized over the intersection of an affine set and the product of second-order (quadratic) cones. SOCPs are nonlinear convex problems that ...
A wide variety of nonlinear convex optimization problems can be cast as problems involving linear matrix inequalities (LMIs), and hence efficiently solved using recently developed interior-point metho...
In this talk I will give an overview of some major developments in convex optimization that have emerged over the last ten years or so. The basic idea is that convex problems are fundamentally tractab...
In this tutorial paper, we consider the problem of minimizing the rank of a matrix over a convex set. The Rank Minimization Problem (RMP) arises in diverse areas such as control, system identification...
Geometric programming (GP) describes a type of optimization problem that has been known since the 1970s, but recently has attracted more attention for several reasons. The first is the development of ...
Motivated by applications to sensor, peer-to-peer and ad hoc networks, we study distributed asynchronous algorithms, also known as gossip algorithms, for computation and information exchange in an arb...
Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical mod...
Consider a sequence X = (Xn: n ≥ 1)of independent and identically distributed random variables, and an independent geometrically distributed random variable M with parameter p. The random variable SM ...
This paper describes the reference architecture to support a multi-user virtual healthcare network that enables rehabilitation and social reintegration of people with disabilities. The network, based ...

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