Inference and Learning from Data: Volume 2

ISBN-13: 9781009218269 / Angielski / Twarda / 2022 / 1070 str.

Ali H. (Ecole Polytechnique Federale de Lausanne) Sayed

Opis

Discover techniques for inferring unknown variables and quantities with the second volume of this extraordinary three-volume set.

Recenzje

'The book series is timely and indispensable. It is a unique companion for graduate students and early-career researchers. The three volumes provide an extraordinary breadth and depth of techniques and tools, and encapsulate the experience and expertise of a world-class expert in the field. The pedagogically crafted text is written lucidly, yet never compromises rigor. Theoretical concepts are enhanced with illustrative figures, well-thought problems, intuitive examples, datasets, and MATLAB codes that reinforce readers' learning.' Abdelhak Zoubir, TU Darmstadt

Spis treści

Preface; Notation; 27. Mean-Square-Error inference; 28. Bayesian inference; 29. Linear regression; 30. Kalman filter; 31. Maximum likelihood; 32. Expectation maximization; 33. Predictive modeling; 34. Expectation propagation; 35. Particle filters; 36. Variational inference; 37. Latent Dirichlet allocation; 38. Hidden Markov models; 39. Decoding HMMs; 40. Independent component analysis; 41. Bayesian networks; 42. Inference over graphs; 43. Undirected graphs; 44. Markov decision processes; 45. Value and policy iterations; 46. Temporal difference learning; 47. Q-learning; 48. Value function approximation; 49. Policy gradient methods; Author index; Subject index.