Search results for "Optimization" - Rhea

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• Lecture 12 - Support Vector Machine and Quadratic Optimization Problem Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]], This gives a [[Quadratic Optimization Problem_Old Kiwi]]: Minimize <math>\frac{1}{2}||\vec{c}||^2</math> subject
  8 KB (1,235 words) - 07:49, 17 January 2013
• AC-3: Optimization Old Kiwi
  112 B (16 words) - 11:07, 22 March 2008
• Lecture 12 - Support Vector Machine and Quadratic Optimization Problem OldKiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_OldKiwi|12]]| This gives a [[Quadratic Optimization Problem_OldKiwi]]: Minimize <math>\frac{1}{2}||\vec{c}||^2</math> subject t
  8 KB (1,278 words) - 10:19, 10 June 2013

Page text matches

• HKNQE Automatic Controls
  ==Optimization==
  214 B (21 words) - 10:35, 3 December 2008
• Meta Course List
  *[[MA421|MA 421]]:"Linear Programming and Optimization Techniques"
  4 KB (474 words) - 06:08, 4 November 2013
• ECE662:BoutinSpring08 Old Kiwi
  * [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi]]
  6 KB (747 words) - 04:18, 5 April 2013
• ECE662:Glossary Old Kiwi
  ...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 (4,832 words) - 17:13, 22 October 2010
• Clustering Old Kiwi
  * '''Optimization-based methods'''
  8 KB (1,173 words) - 11:41, 26 April 2008
• Lecture 17 - Nearest Neighbors Clarification Rule and Metrics Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  6 KB (938 words) - 07:38, 17 January 2013
• Lecture 1 - Introduction Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  3 KB (468 words) - 07:45, 17 January 2013
• Lecture 2 - Decision Hypersurfaces Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  5 KB (737 words) - 07:45, 17 January 2013
• Lecture 3 - Bayes classification Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  5 KB (843 words) - 07:46, 17 January 2013
• Lecture 5 - Discriminant Functions Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  6 KB (916 words) - 07:47, 17 January 2013
• Lecture 6 - Discriminant Functions Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  9 KB (1,586 words) - 07:47, 17 January 2013
• Lecture 7 - MLE and BPE Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  10 KB (1,488 words) - 09:16, 20 May 2013
• Lecture 8 - MLE, BPE and Linear Discriminant Functions Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  5 KB (792 words) - 07:48, 17 January 2013
• Lecture 9 - Linear Discriminant Functions Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  8 KB (1,307 words) - 07:48, 17 January 2013
• Lecture 10 - Batch Perceptron and Fisher Linear Discriminant Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  5 KB (755 words) - 07:48, 17 January 2013
• Lecture 11 - Fischer's Linear Discriminant again Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  5 KB (907 words) - 07:49, 17 January 2013
• Lecture 12 - Support Vector Machine and Quadratic Optimization Problem Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]], This gives a [[Quadratic Optimization Problem_Old Kiwi]]: Minimize <math>\frac{1}{2}||\vec{c}||^2</math> subject
  8 KB (1,235 words) - 07:49, 17 January 2013
• Lecture 13 - Kernel function for SVMs and ANNs introduction Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]], Previous: [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi]]; Next: [[Lecture 14 - ANNs, Non-parametric Density Estim
  8 KB (1,354 words) - 07:51, 17 January 2013
• Lecture 14 - ANNs, Non-parametric Density Estimation (Parzen Window) Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  13 KB (2,073 words) - 07:39, 17 January 2013
• Lecture 15 - Parzen Window Method Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  7 KB (1,212 words) - 07:38, 17 January 2013
• Lecture 16 - Parzen Window Method and K-nearest Neighbor Density Estimate Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  10 KB (1,607 words) - 07:38, 17 January 2013
• Old QE question numbering Old Kiwi
  |ee580 || AC-3 || (AC-2) || Optimization
  2 KB (279 words) - 22:00, 9 March 2008
• Lecture 18 - Nearest Neighbors Clarification Rule and Metrics(Continued) Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  6 KB (1,066 words) - 07:40, 17 January 2013
• Support Vector Machines Old Kiwi
  ...Old Kiwi|Lecture 11]], [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|Lecture 12]] and [[Lecture 13 - Kernel function for SVMs a
  3 KB (366 words) - 07:48, 10 April 2008
• ECE662:ChangeLog Old Kiwi
  * 2008/04/20 -- Added four papers in [[Publications_Old Kiwi]] about Optimization-based clustering methods.
  10 KB (1,418 words) - 11:21, 28 April 2008
• Feature Extraction Old Kiwi
  A global optimization technique is introduced for statistical classifier design to minimize the p
  3 KB (430 words) - 09:40, 24 April 2008
• Genetic algorithms Old Kiwi
  GA is widely used as a optimization technique. Other biological inspired techniques include Ant Colony Optimisa
  2 KB (254 words) - 21:51, 10 March 2008
• Publications Old Kiwi
  ===Optimization-based clustering methods=== ...that follows the min-max clustering principle. The relaxed version of the optimization of the min-max cut objective function leads to the Fiedler vector in spectr
  39 KB (5,715 words) - 09:52, 25 April 2008
• Derivation of Fisher's Linear Discriminant Old Kiwi
  Need to fix <math>|| \omega || = 1</math> , resulting in a Constrained Optimization Problem.
  4 KB (653 words) - 09:50, 22 April 2008
• Lecture 4 - Bayes Classification Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  8 KB (1,360 words) - 07:46, 17 January 2013
• Genetic algorithm Old Kiwi
  ...cal inspired techniques include Ant Colony Optimization and Particle Swarm Optimization.
  2 KB (253 words) - 23:42, 21 March 2008
• Gradient Descent Old Kiwi
  [[Category:Optimization]]
  1 KB (201 words) - 09:46, 24 March 2008
• Lecture 19 - Nearest Neighbor Error Rates Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  5 KB (1,003 words) - 07:40, 17 January 2013
• Lecture 20 - Density Estimation using Series Expansion and Decision Trees Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  6 KB (1,047 words) - 07:42, 17 January 2013
• Lecture 21 - Decision Trees(Continued) Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]], Query selection => numerical optimization problem.
  6 KB (1,012 words) - 07:42, 17 January 2013
• Lecture 22 - Decision Trees and Clustering Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  6 KB (806 words) - 07:42, 17 January 2013
• Lagrange Multipliers Old Kiwi
  ...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
  448 B (72 words) - 09:19, 7 April 2008
• Lecture 23 - Spanning Trees Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  7 KB (1,060 words) - 07:43, 17 January 2013
• Lecture 24 - Clustering and Hierarchical Clustering Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  8 KB (1,254 words) - 07:43, 17 January 2013
• Fuzzy C-means Old Kiwi
  ...d data and the center. Fuzzy partition is carried out through an iterative optimization of the previous expression with the update of membership <math>u_{ij}</math
  1 KB (258 words) - 15:20, 10 April 2008
• Lecture 25 - Clustering Algorithms Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]], to speed up optimization of J
  8 KB (1,259 words) - 07:43, 17 January 2013
• Penalty Methods Old Kiwi
  ...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) - 00:44, 17 April 2008
• Lecture 26 - Statistical Clustering Methods Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  8 KB (1,244 words) - 07:44, 17 January 2013
• Lecture 27 - Clustering by finding valleys of densities Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  8 KB (1,337 words) - 07:44, 17 January 2013
• Lecture 28 - Final lecture Old Kiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_Old Kiwi|12]],
  10 KB (1,728 words) - 07:55, 17 January 2013
• Quadratic Programming Problem Old Kiwi
  A linearly constrained optimization problem with a quadratic objective function is called a quadratic program (
  232 B (35 words) - 22:24, 24 April 2008
• Slack Variable Old Kiwi
  ...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) - 22:25, 24 April 2008
• Neural Networks using Genetic Algorithms Old Kiwi
  ...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) - 10:51, 25 April 2008
• Lecture 2 - Decision Hypersurfaces OldKiwi
  [[Lecture 12 - Support Vector Machine and Quadratic Optimization Problem_OldKiwi|12]]|
  5 KB (744 words) - 10:17, 10 June 2013
• ECE662:BoutinSpring08 OldKiwi
  ...mization Problem_OldKiwi|Lecture 12 - Support Vector Machine and Quadratic Optimization Problem]]
  7 KB (875 words) - 06:11, 13 February 2012