Iterative Methods
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Iterative Methods: First Order Methods, Optimization Methods, Iterative Method, Expectation-Maximization Algorithm

Iterative Methods: First Order Methods, Optimization Methods, Iterative Method, Expectation-Maximization Algorithm


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About the Book

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 41. Chapters: First order methods, Optimization methods, Iterative method, Expectation-maximization algorithm, Levenberg-Marquardt algorithm, Gauss-Newton algorithm, Gradient descent, Derivation of the conjugate gradient method, Euler method, Luus-Jaakola, BFGS method, Cutting-plane method, Golden section search, Discretization, Karmarkar's algorithm, Newton's method in optimization, Nonlinear programming, Quasi-Newton method, Interior point method, Simultaneous perturbation stochastic approximation, L-BFGS, WORHP, Nonlinear conjugate gradient method, Kantorovich theorem, Frank-Wolfe algorithm, Trust region, Schild's ladder, Linear approximation, Line search, Sequential quadratic programming, Davidon-Fletcher-Powell formula, IPOPT, Successive parabolic interpolation, SR1 formula, Powell's method, Local convergence, Optimization algorithm. Excerpt: In statistics, an expectation-maximization (EM) algorithm is a method for finding maximum likelihood or maximum a posteriori (MAP) estimates of parameters in statistical models, where the model depends on unobserved latent variables. EM is an iterative method which alternates between performing an expectation (E) step, which computes the expectation of the log-likelihood evaluated using the current estimate for the parameters, and a maximization (M) step, which computes parameters maximizing the expected log-likelihood found on the E step. These parameter-estimates are then used to determine the distribution of the latent variables in the next E step. The EM algorithm was explained and given its name in a classic 1977 paper by Arthur Dempster, Nan Laird, and Donald Rubin. They pointed out that the method had been "proposed many times in special circumstances" by earlier authors. In particular, a very detailed treatment of the EM method for exponential families was published by Rolf Sund...


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Product Details
  • ISBN-13: 9781233063109
  • Publisher: Books LLC, Wiki Series
  • Publisher Imprint: Books LLC, Wiki Series
  • Height: 246 mm
  • No of Pages: 42
  • Spine Width: 2 mm
  • Weight: 95 gr
  • ISBN-10: 1233063103
  • Publisher Date: 17 Aug 2011
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Sub Title: First Order Methods, Optimization Methods, Iterative Method, Expectation-Maximization Algorithm
  • Width: 189 mm


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