Machine Learning Summer School (MLSS), Tübingen 2003

Machine Learning Summer School (MLSS), Tübingen 2003

16 Lectures · Aug 3, 2003

About

Machine Learning is a foundational discipline of the Information Sciences. It combines deep theory from areas as diverse as Statistics, Mathematics, Engineering, and Information Technology with many practical and relevant real life applications.

The aim of the summer school is to cover the entire spectrum from theory to practice. It is mainly targeted at research students, IT professionals, and academics from all over the world.

//Disclaimer:// VideoLectures.NET emphasizes that we are not authors of these videos and we are not taking responsibility for the low quality of these videos. They were uploaded due to their content value in the scientific field of Computer Science and published with the permission of the organizers.

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Lectures

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02:53:47

Monte Carlo Simulation methods

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Statistical Learning Theory

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Independent Component Analysis

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Gaussian Processes

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Bioinformatics

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Stochastic Learning

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Concentration Inequalities with Machine Learning Applications

Stéphane Boucheron

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Some Mathematical Tools for Machine Learning

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Universal Modeling: Introduction to modern MDL

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Information Retrieval and Language Technology

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Foundations of Learning

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04:11:41

Unsupervised Learning with Kernels

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Bayesian Inference: Principles and Practice

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02:11:43

An Introduction to Pattern Classification

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Empirical Inference

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Analysis of Support Vector Machine Classification

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Lecture