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比利时vs摩洛哥足彩 ,
university of california san diego

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math 278c - optimization seminar and mathematics colloquium

jong-shi pang

university of southern california

on the pervasiveness of difference-convexity in optimization and statistics

abstract:

with the increasing interest in applying the methodology of difference-of-convex (dc) optimization to diverse problems in engineering and statistics, we show that many well-known functions arising therein can be represented as the difference of two convex functions. these include a univariate folded concave function commonly employed in statistical learning, the value function of a copositive recourse function in two-stage stochastic programming, and many composite statistical functions in risk analysis, such as the value-at-risk (var), conditional value-at-risk (cvar), expectation-based, var-based, and cvar-based random deviation functionals. we also discuss decomposition methods for computing directional stationary points of a class of nonsmooth, nonconvex dc programs that combined the gauss-seidel idea, the alternating direction method of multipliers, and a special technique to handle the negative of a pointwise max function.

host: jiawang nie

april 20, 2017

4:00 pm

ap&m 6402

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