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: Elements of Causal Inference: Foundations and Learning AlgorithmsElements of Causal Inference: Foundations and Learning Algorithms
by - The MIT Press
This book offers a self-contained and concise introduction to causal models and how to learn them from data. The book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from data ...
(2346 views)
Book cover: Machine Learning for Data StreamsMachine Learning for Data Streams
by - The MIT Press
This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA, allowing readers to try out the techniques after reading the explanations.
(2620 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.
(4462 views)
Book cover: Statistical Foundations of Machine LearningStatistical Foundations of Machine Learning
by
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice.
(5554 views)