Statistical Learning and Sequential Prediction
by Alexander Rakhlin, Karthik Sridharan
Publisher: University of Pennsylvania 2014
Number of pages: 261
Description:
This course will focus on theoretical aspects of Statistical Learning and Sequential Prediction. The minimax approach, which we emphasize throughout the course, offers a systematic way of comparing learning problems. Beyond the theoretical analysis, we will discuss learning algorithms and, in particular, an important connection between learning and optimization.
Download or read it online for free here:
Download link
(2.5MB, PDF)
Similar books
Inductive Logic Programming: Theory and Methodsby Stephen Muggleton, Luc de Raedt - ScienceDirect
Inductive Logic Programming is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge. The authors survey the most important theories and methods of this new field.
(32959 views)
Introduction to Machine Learning for the Sciencesby Titus Neupert, et al. - arXiv.org
This is an introductory machine learning course specifically developed with STEM students in mind, written by the theoretical Condensed Matter Theory group at the University of Zurich. We discuss supervised, unsupervised, and reinforcement learning.
(1832 views)
Machine Learningby Abdelhamid Mellouk, Abdennacer Chebira - InTech
Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization, linear subspace learning for facial expression analysis, and more.
(14736 views)
Introduction to Machine Learningby Amnon Shashua - arXiv
Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).
(20751 views)