Campus Event Calendar
Event Entry
What and Who
Machine Learning and Applications
Prof Dr Klaus-Robert Müller
TU Berlin und Fraunhofer FIRST
Distinguished Speaker Series Max
Planck Institute for Informatics and Cluster of Excellence Multimodal Computing and Interaction
AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, RG2
Public Audience
English
Note: We use this to send email in the morning.
Date, Time and Location
Monday, 23 June 2008
14:00
45 Minutes
E1 4
024
Saarbrücken
Abstract
This lecture provides a very brief introduction to Support Vector
Machines as an example for successful kernel-based machine learning (ML)
and touches on fundamentally open issues in this field.
Then I review in short selected successful applications of kernel
based ML, i.e.for hacker intrusion detection,
computational chemistry etc.
The main part of my talk will discuss ML methods for the online
analysis of brain signals, i.e.~I chart the path towards an EEG-based
Brain Computer Interface.
Brain Computer Interfacing (BCI) aims at making use of brain signals
for e.g. the control of objects, spelling, gaming and so on. In
particular the talk will show the wealth, the complexity and the
difficulties of the data available, a truely enormous challenge: In
real-time a multi-variate very strongly noise contaminated data stream
is to be processed and neuroelectric activities are to be accurately
differentiated.
Finally, I report in more detail about the Berlin Brain Computer
(BBCI) Interface that is based on EEG signals and take the audience
all the way from the measured signal, the preprocessing and filtering,
the classification to the respective application. BCI as a
fascinating new channel for man-machine communication is discussed in
a clincial setting and for human machine interaction.
Machines as an example for successful kernel-based machine learning (ML)
and touches on fundamentally open issues in this field.
Then I review in short selected successful applications of kernel
based ML, i.e.for hacker intrusion detection,
computational chemistry etc.
The main part of my talk will discuss ML methods for the online
analysis of brain signals, i.e.~I chart the path towards an EEG-based
Brain Computer Interface.
Brain Computer Interfacing (BCI) aims at making use of brain signals
for e.g. the control of objects, spelling, gaming and so on. In
particular the talk will show the wealth, the complexity and the
difficulties of the data available, a truely enormous challenge: In
real-time a multi-variate very strongly noise contaminated data stream
is to be processed and neuroelectric activities are to be accurately
differentiated.
Finally, I report in more detail about the Berlin Brain Computer
(BBCI) Interface that is based on EEG signals and take the audience
all the way from the measured signal, the preprocessing and filtering,
the classification to the respective application. BCI as a
fascinating new channel for man-machine communication is discussed in
a clincial setting and for human machine interaction.
Contact
Roxane Wetzel
900
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Roxane Wetzel, 06/16/2008 10:40
Roxane Wetzel, 05/30/2008 13:32
Roxane Wetzel, 05/30/2008 13:04 -- Created document.
Roxane Wetzel, 05/30/2008 13:32
Roxane Wetzel, 05/30/2008 13:04 -- Created document.