Logo

Statistical Learning and Sequential Prediction

Small book cover: Statistical Learning and Sequential Prediction

Statistical Learning and Sequential Prediction
by

Publisher: University of Pennsylvania
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

Book cover: The Elements of Statistical Learning: Data Mining, Inference, and PredictionThe Elements of Statistical Learning: Data Mining, Inference, and Prediction
by - Springer
This book brings together many of the important new ideas in learning, and explains them in a statistical framework. The authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties.
(40228 views)
Book cover: Modeling Agents with Probabilistic ProgramsModeling Agents with Probabilistic Programs
by - AgentModels.org
This book describes and implements models of rational agents for (PO)MDPs and Reinforcement Learning. One motivation is to create richer models of human planning, which capture human biases. The book assumes basic programming experience.
(5770 views)
Book cover: A Survey of Statistical Network ModelsA Survey of Statistical Network Models
by - arXiv
We begin with the historical development of statistical network modeling and then we introduce some examples in the network literature. Our subsequent discussion focuses on prominent static and dynamic network models and their interconnections.
(8464 views)
Book cover: The Hundred-Page Machine Learning BookThe Hundred-Page Machine Learning Book
by
This is the first successful attempt to write an easy to read book on machine learning that isn't afraid of using math. It's also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
(8917 views)