'Linear equality constraints' presentation slideshows

NLP

893 views • 58 slides

Factorial Mixture of Gaussians and the Marginal Independence Model

Factorial Mixture of Gaussians and the Marginal Independence Model. Ricardo Silva silva@statslab.cam.ac.uk Joint work-in-progress with Zoubin Ghahramani. Goal. To model sparse distributions subject to marginal independence constraints. Why?. X1. X2. Y1. Y2. Y3. Y4. Y5. Why?. X1. X2.

578 views • 45 slides

Factorial Mixture of Gaussians and the Marginal Independence Model

Factorial Mixture of Gaussians and the Marginal Independence Model. Ricardo Silva silva@statslab.cam.ac.uk Joint work-in-progress with Zoubin Ghahramani. Goal. To model sparse distributions subject to marginal independence constraints. Why?. X1. X2. Y1. Y2. Y3. Y4. Y5. Why?. X1. X2.

464 views • 45 slides

Chapter 4 Sensitivity Analysis, Duality and Interior Point Methods

Chapter 4 Sensitivity Analysis, Duality and Interior Point Methods. Interior Point Methods. Simplex methods reach the optimal solution by traversing a series of basic solutions. The path followed by the algorithm moves around the boundary of the feasible region.

655 views • 39 slides

Searching a Linear Subspace

Searching a Linear Subspace. Lecture VI. Deriving Subspaces. There are several ways to derive the nullspace matrix (or kernel matrix). The methodology developed on in our last meeting is referred to the Variable Reduction Technique . The nullspace is then defined as

358 views • 27 slides

NNLS (Lawson-Hanson) method in linearized models

NNLS (Lawson-Hanson) method in linearized models. LSI & NNLS. LSI = Least square with linear equality constraints NNLS = nonnegative least square . Flowchart. Initial conditions. Sets Z and P Variables indexed in the set Z are held at value zero

393 views • 20 slides