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Mathematical optimization
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#	Item
361	APPROXIMATE DYNAMIC PROGRAMMING A SERIES OF LECTURES GIVEN AT TSINGHUA UNIVERSITY JUNE 2014 DIMITRI P. BERTSEKAS Based on the books: Add to Reading List Source URL: athenasc.com Language: English - Date: 2014-06-21 10:19:49 Mathematical optimization Operations research Equations Optimal control Dynamic programming Dimitri Bertsekas Bellman equation Optimization problem Algorithm Reinforcement learning
362	Sutra: International Journal of Mathematical Science Education, Technomathematics Research Foundation Vol. 1, No. 1, , 2008 CLASS-ROOM NOTES: OPTIMIZATION PROBLEM SOLVING - I Add to Reading List Source URL: www.tmrfindia.org Language: English - Date: 2008-11-10 09:49:21 Matroid theory Matroid Weighted matroid Uniform matroid Graphic matroid Greedy algorithm Dynamic programming Greedoid Matroid minor
363	Sensor Localization with Deterministic Accuracy Guarantee Ryo Sugihara Rajesh K. Gupta Add to Reading List Source URL: mesl.ucsd.edu Language: English - Date: 2011-04-30 19:20:57 Operations research Linear programming Mathematical optimization Real algebraic geometry Semidefinite programming Routing algorithms
364	Stochastic Economic Growth: An Operator-Theoretic Approach John Stachurski Submitted in fulfillment of the requirements Add to Reading List Source URL: johnstachurski.net Language: English - Date: 2016-06-19 06:01:55 Markov processes Graph theory Markov chain Stochastic processes Stochastic Mathematical optimization Mathematical model Peyton Young
365	Chapter 3 Tree- based Regress ion This chapter describes two different approaches to induce regression trees. We first present the standard methodology based on the minimisation of the squared error. Least squares (LS) r Add to Reading List Source URL: www.dcc.fc.up.pt Language: English - Date: 2012-12-13 10:18:43 Regression analysis Econometrics Estimation theory Mathematical optimization Decision trees Decision tree learning Linear regression Least squares Least absolute deviations Multivariate adaptive regression splines Predictive analytics
366	Optimization of high-performance monocentric lenses Igor Stamenov,* Ilya Agurok, and Joseph E. Ford Department of Electrical and Computer Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, Cali Add to Reading List Source URL: psilab.ucsd.edu Language: English - Date: 2015-01-09 12:29:41 Optics Geometrical optics Operations research Mathematical optimization Global optimization Lens Optical aberration Optical lens design Camera lens Calculation of glass properties Energy minimization Zemax
367	ExcEEding valuE VALUE IS WHAT YOU GET Warren Buffet said, “Price is what you pay. Value is what you get.” The project budget, schedule, and specifications constitute the project’s price. In other words, price compr Add to Reading List Source URL: www.standishgroup.com Language: English - Date: 2014-08-25 14:46:24 Management Financial economics Mathematical finance Marketing Portfolio optimization Project management Value Project portfolio management
368	Experimental evaluation of modern variable selection strategies in Constraint Satisfaction Problems Thanasis Balafoutis1 and Kostas Stergiou1 Department of Information & Communication Systems Engineering University of th Add to Reading List Source URL: ceur-ws.org Language: English - Date: 2008-11-28 08:00:26 Constraint programming Operations research Constraint satisfaction problem Local consistency Mathematical optimization Heuristic Integer programming Constraint satisfaction Search algorithm Local search Look-ahead Decomposition method
369	Graph Drawing by Stress Majorization Emden R. Gansner, Yehuda Koren and Stephen North AT&T Labs — Research Florham Park, NJ 07932 {erg,yehuda,north}@research.att.com Abstract. One of the most popular graph drawing meth Add to Reading List Source URL: www.research.att.com Language: English - Date: 2009-11-17 10:55:58 Multivariate statistics Graph drawing Mathematical analysis Mathematical optimization Stress majorization Force-directed graph drawing Numerical linear algebra Majorization Multidimensional scaling Graph theory Cholesky decomposition Line graph
370	CS261: A Second Course in Algorithms Lecture #9: Linear Programming Duality (Part 2)∗ Tim Roughgarden† February 2, Add to Reading List Source URL: theory.stanford.edu Language: English - Date: 2016-02-16 22:56:26 Mathematical optimization Convex optimization Linear programming Operations research Duality Weak duality Strong duality Constraint Duality gap Semidefinite programming

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