CS168: The Modern Algorithmic Toolbox Lecture #18: Linear and Convex Programming, with Applications to Sparse Recovery Tim Roughgarden & Gregory Valiant∗ May 25, 2016

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Duality for increasing convex functionals with countably many marginal constraints D. Bartl∗ P. Cheridito†

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• LP-type problem
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• Mathematical optimization
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• Linear programming
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• Interior point method
• Duality
• Network simplex algorithm
• Linear complementarity problem
• KarushKuhnTucker conditions
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ONE-ONE FUNCTIONS AND INVERSES MATH 152, SECTION 55 (VIPUL NAIK) Corresponding material in the book: Section 7.1. What students should definitely get: The definition of one-to-one function, the computational and checking

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• Functions and mappings
• Inverse function
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• Injective function
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A THEORY OF THE CARTOGRAPHIC LINE Thomas K. Peucker Simon Fraser University

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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
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• Price of anarchy
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A combination of convex programs developed by Chan- drasekaran, Parillo and Wilskyand Saunderson et alcan be used to extract financial risk factors from a sample return covariance matrix. I will examine

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