**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 Methods**

by

**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 Sciences**

by

**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 Learning**

by

**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 Learning**

by

**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)