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Convex
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281	A APPENDIX Proof sketch of Corollary 4.5. The proof follows similarly to Theorem 4.2. But, here the terms fti (y, θ) and fto (y, θ) are slightly different Add to Reading List Source URL: marek.petrik.us Language: English - Date: 2016-07-14 09:59:52 Convex analysis Convex function
282	Journal of Risk and Uncertainty, 16:2 147–) © 1998 Kluwer Academic Publishers Stochastic Dominance and Prospect Dominance with Subjective Weighting Functions HAIM LEVY Add to Reading List Source URL: pluto.mscc.huji.ac.il Language: English - Date: 2014-02-02 05:57:49 Decision theory Stochastic dominance Probability distributions Mathematical finance Functions and mappings Financial risk Data transformation Normal distribution Cumulative distribution function Marginal conditional stochastic dominance Convex function Derivative
283	JuliaOpt Optimization packages in Julia Iain Dunning Operations Research Center MIT Add to Reading List Source URL: iaindunning.com Language: English - Date: 2015-08-12 01:24:20 Mathematical optimization Numerical software Mathematical modeling Operations research Convex optimization AMPL Conic optimization SCIP Nl Julia TOMLAB LINGO
284	75 Documenta Math. Who Solved the Hirsch Conjecture? ¨ nter M. Ziegler Add to Reading List Source URL: www.math.uiuc.edu Language: English - Date: 2012-07-25 10:24:45 Convex geometry Polytopes Linear programming Operations research Polyhedral combinatorics Hirsch conjecture KleeMinty cube Simplex algorithm Convex polytope Simplex 4-polytope Simple polytope
285	We propose a new class of convex penalty functions, called variational Gram functions (VGFs), that can promote pairwise relations, such as orthogonality, among a set of vectors in a vector space. These functions can serv Add to Reading List Source URL: mmds-data.org - Date: 2016-06-23 15:50:48
286	Monotone transports Convergence Semi-discrete evolution Continuous evolution From Brenier to Kntohe and from Knothe to Add to Reading List Source URL: tommi.imag.fr Language: English - Date: 2014-04-22 07:16:21 Measure theory Order theory Calculus of variations Transportation theory Monotonic function Convex function Mathematical optimization Cumulative distribution function
287	Microsoft Word - NEW17.docx Add to Reading List Source URL: agecon2.tamu.edu Language: English - Date: 2013-08-28 16:06:46 Operations research Mathematical optimization Convex optimization Linear programming Reduced cost Numerical software Draft:Extended mathematical programming PROPT
288	Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction Stephen H. Bach Bert Huang Add to Reading List Source URL: psl.umiacs.umd.edu Language: English - Date: 2013-11-10 21:52:40 Graphical models Markov models Probability theory Markov random field Structured prediction Bayesian network Random field Markov chain Support vector machine Markov logic network Algorithm Hidden Markov model
289	DISTRIBUTED ALGORITHMS FOR SPARSE RECONSTRUCTION João Mota Instituto Superior Técnico Lisbon, Portugal ABSTRACT Many applications require the knowledge of a sparse linear Add to Reading List Source URL: users.isr.ist.utl.pt Language: English - Date: 2008-11-21 11:04:05 Convex optimization Operations research Mathematical optimization Numerical linear algebra Subgradient method Linear programming Interior point method
290	Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization Stephen H. Bach University of Maryland, College Park College Park, MD 20742 Add to Reading List Source URL: psl.umiacs.umd.edu Language: English - Date: 2013-06-14 19:26:47 Operations research Mathematical optimization Convex optimization Multivariable calculus Linear programming Lagrange multiplier Finite element method Algorithm Interior point method

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