• [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]], to speed up optimization of J
    8 KB (1,259 words) - 08:43, 17 January 2013
  • ...roblems. It can be shown that the solutions of these derived unconstrained optimization problems will converge to the solution of the original constrained problem.
    577 B (83 words) - 01:44, 17 April 2008
  • [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
    8 KB (1,244 words) - 08:44, 17 January 2013
  • [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
    8 KB (1,337 words) - 08:44, 17 January 2013
  • [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
    10 KB (1,728 words) - 08:55, 17 January 2013
  • A linearly constrained optimization problem with a quadratic objective function is called a quadratic program (
    232 B (35 words) - 23:24, 24 April 2008
  • ...equality constraint. This procedure is often performed to formulate linear optimization problems into a form which can be efficiently solve using a fast algorithm:
    474 B (75 words) - 23:25, 24 April 2008
  • ...wiki/Genetic_algorithm) are a method of determining the best solutions for optimization and search problems by means of evolution using simulations. The steps are
    2 KB (288 words) - 11:51, 25 April 2008
  • [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_OldKiwi|12]]|
    5 KB (744 words) - 11:17, 10 June 2013
  • ...mization Problem_OldKiwi|Lecture 12 - Support Vector Machine and Quadratic Optimization Problem]]
    7 KB (875 words) - 07:11, 13 February 2012
  • Signals and Systems, 3rd edition, N. Levan, Optimization Software, Inc., New York, ISBN 0-911575-63-4, 1992.
    7 KB (1,153 words) - 14:06, 24 August 2009
  • [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_OldKiwi|12]]|
    9 KB (1,341 words) - 11:15, 10 June 2013
  • ...o solve. So, fix <math>|\vec{w}|=1</math>, but then this is a "constraint optimization problem" (did i screw up this description? --[[User:Mreeder|Mreeder]] 21:56
    9 KB (1,536 words) - 07:26, 12 April 2010
  • ...s" in the case where the data is not linearly separable. We noted that the optimization problem in that case involves inner products between the training samples,
    1 KB (188 words) - 10:36, 16 April 2010
  • ...alytically or numerically minimizing <math>e^{-f(\beta)}</math>, therefore optimization is now in the one dimensional β space.
    5 KB (806 words) - 09:08, 11 May 2010
  • =[[MA421]]: "Linear Programming and Optimization Techniques"= "optimization problems". In all cases, one wants to minimize or maximize a
    2 KB (266 words) - 07:29, 4 January 2011
  • ...to one or more constraints; it is the basic tool in nonlinear constrained optimization. Simply put, the technique is able to determine where on a particular set o ...roblems. It can be shown that the solutions of these derived unconstrained optimization problems will converge to the solution of the original constrained problem.
    31 KB (4,787 words) - 18:21, 22 October 2010
  • =MA421: "Linear Programming and Optimization Techniques"=
    768 B (100 words) - 11:33, 11 November 2010
  • ...lly use as one of the optimization problem solvers. In general, to solve a optimization problem, you need to have an objective (what do you want to solve? Do you w There are many software that help you solve optimization problems. In this page, I will focus on how to use GAMS.
    5 KB (736 words) - 09:14, 11 April 2013
  • ...application of signal processing in agriculture, such as yield mapping or optimization of fertilizer or pesticide application. This research is supervised by Prof
    5 KB (721 words) - 12:18, 9 February 2012

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