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Quasiconvex function
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1	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 Add to Reading List Source URL: files.vipulnaik.com Language: English - Date: 2016-08-13 11:33:29 Mathematical analysis Mathematics Calculus Multivariable calculus Differential calculus Convex analysis Mathematical optimization Derivative Lagrange multiplier Quasiconvex function Hessian matrix Gradient
2	REVIEW SHEET FOR FINAL: BASIC MATH 195, SECTION 59 (VIPUL NAIK) The document does not include material that was part of the midterm 1 and midterm 2 review sessions. Please also bring copies of these review sheets to the Add to Reading List Source URL: files.vipulnaik.com Language: English - Date: 2016-08-13 11:33:29 Mathematical analysis Mathematics Analysis Multivariable calculus Differential calculus Mathematical optimization Convex analysis Singularity theory Quasiconvex function Derivative test Critical point Maxima and minima
3	MAXIMUM AND MINIMUM VALUES: EXAMPLES MATH 195, SECTION 59 (VIPUL NAIK) What students should hopefully get: The description of critical points, local extreme values, and absolute extreme values for additively separable fu Add to Reading List Source URL: files.vipulnaik.com Language: English - Date: 2016-08-13 11:33:29 Mathematical analysis Mathematics Analysis Multivariable calculus Differential calculus Mathematical optimization Convex analysis Quasiconvex function Convex function Derivative test Critical point Maxima and minima
4	STATIC OPTIMIZATION (E. Molho) SYLLABUS The usual contents of a basic calculus course and some basic notions in linear algebra are considered as prerequisites for the course. 1) Eigenvalues and eigenvectors, quadratic fo Add to Reading List Source URL: www.laser.unimi.it Language: English - Date: 2014-10-20 11:56:50 Mathematical optimization Quasiconvex function Constrained optimization Mathematical economics Optimization Sequential quadratic programming Trajectory optimization
5	PACORA: Performance Aware Convex Optimization for Resource Allocation Sarah L. Bird, University of California-Berkeley <> Burton J. Smith, Microsoft <> Abstract Resource alloc Add to Reading List Source URL: www.usenix.org Language: English - Date: 2011-04-22 17:11:28 Convex analysis Mathematical optimization Real analysis Convex geometry Convex optimization Convex function Quasiconvex function Convex set Logarithmically convex function ShapleyFolkman lemma
6	A Level-set Hit-and-run Sampler for Quasi-Concave Distributions Shane T. Jensen and Dean P. Foster Department of Statistics, The Wharton School, University of Pennsylvania Abstract Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2014-05-24 19:58:02 Monte Carlo methods Markov chain Monte Carlo Non-uniform random numbers Probability distributions Computational statistics Gibbs sampling Rejection sampling MetropolisHastings algorithm Slice sampling Bayesian network Quasiconvex function Normal distribution
7	Midterm Exam, Econ 210A, FallElmer Kink’s utility function is min{x1 , 2x2 }. Draw a few indifference curves for Elmer. Find each of the following for Elmer: • His Marshallian demand function for each good. Add to Reading List Source URL: econ.ucsb.edu Language: English - Date: 2008-11-03 16:55:56 Concave function Convex function Quasiconvex function Utility Hessian matrix Expected utility hypothesis Insurance Dracula Logarithmically concave function Mathematical analysis Mathematical optimization Convex analysis
8	Name Midterm Exam, Econ 210A, Fall 2010 Answer as many questions as you can. Put your answers on these sheets. Question 1. Let f (x1 , x2 ) = Add to Reading List Source URL: econ.ucsb.edu Language: English - Date: 2010-10-26 16:17:27 Convex analysis Economics Hicksian demand function Marshallian demand function Convex function Quasiconvex function Consumer choice GEC Consumer theory Mathematical analysis Demand
9	Midterm Exam, Econ 210A, FallElmer Kink’s utility function is min{x1 , 2x2 }. Draw a few indifference curves for Elmer. These are L-shaped, with the corners lying on the line x1 = 2x2 . Find each of the follow Add to Reading List Source URL: econ.ucsb.edu Language: English - Date: 2008-11-19 18:29:11 Concave function Convex function Hessian matrix Quasiconvex function PROPT Logarithmically concave function Mathematical analysis Mathematical optimization Convex analysis
10	Risk Sharing in the Small and in the Large Paolo Ghirardato∗ Marciano Siniscalchi† This version February 11, 2015 Add to Reading List Source URL: laef.ucsb.edu Language: English - Date: 2015-02-23 10:44:34 Utility Convex analysis Economics Financial risk Ambiguity aversion Quasiconvex function Expected utility hypothesis Preference Risk aversion Mathematical analysis Game theory Decision theory