Hausdorff Center for Mathematics, Summer School (May 9–13, 2016) Problems for “Discrete Convex Analysis” (by Kazuo Murota) Problem 1. Prove that a function f : Z2 → R defined by f (x1 , x2 ) = φ(x1 − x2 ) is

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Smoothed Analysis of Partitioning Algorithms for Euclidean Functionals∗ Markus Bl¨aser1 Bodo Manthey2

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• Mathematical analysis
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• Generalized functions
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REVIEW SHEET FOR FINAL: ADVANCED MATH 195, SECTION 59 (VIPUL NAIK) To maximize efficiency, please bring a copy (print or readable electronic) of this review sheet to all review sessions. 1. Directional derivatives and gr

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• Mathematical analysis
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• Calculus
• Multivariable calculus
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• Derivative
• Lagrange multiplier
• Quasiconvex function
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• Mathematical optimization
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• Mathematical analysis
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• Inverse function
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• Convex function
• Injective function
• Continuous function
• Derivative
• Bijection
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Algorithms and Data Structures Winter TermExercises for UnitShow that the price of anarchy for routing games with quadratic latency functions `e (x) = x2 is at most

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• Mathematical analysis
• Game theory
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• Mathematics
• Price of anarchy
• Routing
• Convex function

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• Metalworking
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JMLR: Workshop and Conference Proceedings vol 40:1–26, 2015 Escaping the Local Minima via Simulated Annealing: Optimization of Approximately Convex Functions Alexandre Belloni The Fuqua School of Business, Duke Univer

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• Mathematical analysis
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• Logarithmically concave function
• Convex function
• Central limit theorem
• Normal distribution
• Convex optimization
• Expected value
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OPTIMIZATION APPROACHES TO QUADRATURE: NEW CHARACTERIZATIONS OF GAUSSIAN QUADRATURE ON THE LINE AND QUADRATURE WITH FEW NODES ON PLANE ALGEBRAIC CURVES, ON THE PLANE AND IN HIGHER DIMENSIONS CORDIAN RIENER AND MARKUS SCH

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• Algebra
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