Madeleine R. Udell

Learn More
We introduce the Stochastic Asynchronous Proximal Alternating Linearized Minimization (SAPALM) method, a block coordinate stochastic proximal-gradient method for solving nonconvex, nonsmooth optimization problems. SAPALM is the first asynchronous parallel optimization method that provably converges on a large class of nonconvex, nonsmooth problems. We prove(More)
The problem of maximizing a sum of sigmoidal functions over a convex constraint set arises in many application areas. This objective captures the idea of decreasing marginal returns to investment, and has applications in mathematical marketing, network bandwidth allocation, revenue optimization, optimal bidding, and lottery design. We define the sigmoidal(More)
Doctors prescribe drugs for indications that are not FDA approved. Research indicates that 21% of prescriptions filled are for off-label indications. Of those, more than 73% lack supporting scientific evidence. Traditional drug safety alerts may not cover usages that are not FDA approved. Therefore, analyzing patterns of off-label drug usage in the clinical(More)
  • 1