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math.OC2016
Random constraint sampling and duality for convex optimization
William B. Haskell, Yu Pengqian
We are interested in solving convex optimization problems with large numbers of constraints. Randomized algorithms, such as random constraint sampling, have been very successful in…
math.OC2012
Stochastic dominance-constrained Markov decision processes
William B. Haskell, Rahul Jain
We are interested in risk constraints for infinite horizon discrete time Markov decision processes (MDPs). Starting with average reward MDPs, we show that increasing concave stocha…