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.

Home page url

Download or read it online for free here:
Download link
(2.5MB, PDF)

Similar books

Book cover: Optimal and Learning Control for Autonomous RobotsOptimal and Learning Control for Autonomous Robots
by - arXiv.org
The starting point is the formulation of of an optimal control problem and deriving the different types of solutions and algorithms from there. These lecture notes aim at supporting this unified view with a unified notation wherever possible.
(703 views)
Book cover: Algorithms for Reinforcement LearningAlgorithms for Reinforcement Learning
by - Morgan and Claypool Publishers
We focus on those algorithms of reinforcement learning that build on the theory of dynamic programming. We give a comprehensive catalog of learning problems, describe the core ideas, followed by the discussion of their properties and limitations.
(2075 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.
(845 views)
Book cover: Information Theory, Inference, and Learning AlgorithmsInformation Theory, Inference, and Learning Algorithms
by - Cambridge University Press
A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.
(14585 views)