Connectionists: Machine learning summer school 2007

[Arthur Gretton]

               ~*   Invitation to the   *~
 
==*==  Machine Learning Summer School, Tuebingen, 2007 ==*==


Registration is now open for MLSS 2007, the 9th summer school in a
series beginning in 2002. It is intended for students and researchers
alike, who are interested in machine learning. Its goal is to present
some of the topics at the core of modern machine learning, from
fundamentals to state-of-the-art practice.


URL:
     http://www.mlss.cc/tuebingen07/

Dates:
     Monday August 20 - Friday August 31, 2007 (2 weeks)

Location:
     Max Planck Campus, Tuebingen, Germany

Application Deadline:
     April 1st 2007

Past Schools:
     http://www.mlss.cc

Poster:
     http://www.mlss.cc/tuebingen07/poster/

Email contact:
     mlss07 at tuebingen.mpg.de


Topics will be covered both in lectures (4-6 per subject) and in
practical courses (where students will have the chance to implement
methods for themselves), and are taught by world experts in their
fields.  In addition, informal evening talks will cover a variety of
application areas in which machine learning has successfully been
applied. Material is directed both at outstanding participants without
previous knowledge in machine learning, and at those wishing to
broaden their expertise in the area; this includes PhD, Masters, and
advanced undergraduate students, postdocs, academics, and IT
professionals. The MLSS also provides an excellent opportunity for
interaction with top researchers in a broad cross-section of machine
learning disciplines.

Lecture courses
===============

Andrew Blake			Topics in image and video processing

Olivier Bousquet		Statistical learning theory

Nicolo Cesa-Bianchi		Online Learning

Arnaud Doucet			Sequential Monte Carlo methods

Zoubin Ghahramani		Graphical models

Gene Golub			Linear algebra, computations and applications

Carl Rasmussen		        Bayesian inference and Gaussian processes

Gunnar Raetsch			Introduction to bioinformatics

Bernhard Schoelkopf,		Kernel methods
Alexander Smola		

Yoram Singer			Structured learning

Lieven Vandenberghe		Convex Optimisation

 
Practical courses
=================

Joaquin Quinonero Candela	Gaussian Processes

Manuel Davy			Sampling in practice

Matthias Hein,			Spectral Clustering and other graph based algorithms
Ulrike von Luxburg

Matthias Seeger			Variational Bayesian Inference

Yee Whye Teh			Dirichlet Processes


Evening talks
=============

Andreas Dengel			Knowledge management

Uwe Hanebeck			Information Processing in Sensor/Actuator Networks

Oliver Kohlbacher		Bioinformatics

Joachim Weickert		Image analysis and regularization


PhD, Masters, and undergraduate students are eligible for scholarships
that cover registration, accommodation and/or travel costs. Recipients
will be chosen based on academic merit and financial need. Due to
space constraints, we expect only to admit a fraction of all
applicants; however, the lectures will be videotaped and will be
available online through the www.pascal-network.org site.

The summer school will be held for the second time in Tuebingen, a
town with a historic city centre dating from 1500. Tuebingen also
hosts one of Germany's oldest universities, and is the former
residence of Kepler, Melanchthon, Hoelderlin, Hegel, Hesse, and the
current pope. The Max Planck campus is located on a hill overlooking
the old town, and incorporates a common area and garden for informal
interactions between speakers and students.