Diff for "Main/SS12_AKA"

Differences between revisions 16 and 28 (spanning 12 versions)

Anwendungen Kognitiver Algorithmen

Blockseminar

Termine und Dozenten

Termin:	Präsentationen 04.07.2012, 10:00 - 17:00
Termin:	Raum: FR 6046
Verantwortlicher:	Prof. Dr. Klaus-Robert Müller
Betreuer:	Dr. Felix Bießmann, Irene Winkler

Themen

Computerprogramme können nützliche kognitive Fähigkeiten lernen. Dieses Seminar erlaubt eine vertiefende Einarbeitung in spezielle Anwendungsgebiete von Algorithmen aus dem Bereich des Maschinellen Lernens wie etwa automatisierte Informationsextraktion aus Texten, Mustererkennung in hochdimensionalen Daten, explorative Datenanalyse.

Unter Anleitung wird englischsprachige Fachliteratur über ausgewählte Anwendungsbeispiele zu analysieren, kritisch zu evaluieren und verständlich zu präsentieren sein.

Voraussetzungen

Grundlegende Konzepte der Wahrscheinlichkeitsrechnung, Statistik und Linearer Algebra.

Slides der Vorbesprechung

Enthält alle Abstracts der zur Auswahl stehenden Papers. Slides

Papers

Thema	Student	Betreuer
A simplified neuron model as a principal component analyzer	Tongxin Son	Duncan Blythe
Spatiotemporal energy models for the perception of motion
Eigenfaces for Recognition	Min Zheng	Wojciech Samek
Emergence of simple-cell receptive field properties by learning a sparse code for natural images	Gregor Hendel	Duncan Blythe
Gradient-Based Learning Applied to Document Recognition
Matrices, Vector Spaces, and Information Retrieval	David Lassner	Felix Bießmann
Support vector machines for spam categorization	Chengbing Liu	Bettina Mieth
Kernel PCA and De--Noising in Feature Spaces	Sha Huang	Bettina Mieth
Unsupervised Learning by Probabilistic Latent Semantic Analysis
Rapid Object Detection using a Boosted Cascade of Simple Features	Siyun Li	Wojciech Samek
Kernel methods for exploratory pattern analysis: a demonstration on text data	Yi Ding	Felix Bießmann
The non-invasive Berlin Brain-Computer Interface: fast acquisition of effective performance in untrained subjects
Decoding the visual and subjective contents of the human brain	Alexander Muschalle	Felix Bießmann
Invariant visual representation by single neurons in the human brain.

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 Line 7:
-||<|2> '''Termin:''' ||Präsentationen 04.07.2012, 10:00 - 13:00 ||
+||<|2> '''Termin:''' ||Präsentationen 04.07.2012, 10:00 - 17:00 ||
 Line 27:
-|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Oja1982.pdf|A simplified neuron model as a principal component analyzer]] || Tongxin Son ||  ||
+|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Oja1982.pdf|A simplified neuron model as a principal component analyzer]] || Tongxin Son || Duncan Blythe ||
 Line 29:
-|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Turk1991.pdf|Eigenfaces for Recognition]]|| Min Zheng|| ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Olshausen1996.pdf|Emergence of simple-cell receptive field properties by learning a sparse code for natural images]]|| || ||
+|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Turk1991.pdf|Eigenfaces for Recognition]]|| Min Zheng||  Wojciech Samek ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Olshausen1996.pdf|Emergence of simple-cell receptive field properties by learning a sparse code for natural images]]|| Gregor Hendel || Duncan Blythe ||
 Line 32:
-|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Berry1999.pdf|Matrices, Vector Spaces, and Information Retrieval]]|| || ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Drucker1999.pdf|Support vector machines for spam categorization]]||Chengbing Liu || ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Mika1998.pdf|Kernel PCA and De--Noising in Feature Spaces]]|| Sha Huang|| ||
+|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Berry1999.pdf|Matrices, Vector Spaces, and Information Retrieval]]|| David Lassner || Felix Bießmann ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Drucker1999.pdf|Support vector machines for spam categorization]]||Chengbing Liu ||Bettina Mieth ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Mika1998.pdf|Kernel PCA and De--Noising in Feature Spaces]]|| Sha Huang||Bettina Mieth||
 Line 36:
-|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Viola2001.pdf|Rapid Object Detection using a Boosted Cascade of Simple Features]]||Siyun Li || ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/DeBie2004.pdf|Kernel methods for exploratory pattern analysis: a demonstration on text data]]|| Yi Ding || ||
+|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Viola2001.pdf|Rapid Object Detection using a Boosted Cascade of Simple Features]]||Siyun Li || Wojciech Samek||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/DeBie2004.pdf|Kernel methods for exploratory pattern analysis: a demonstration on text data]]|| Yi Ding || Felix Bießmann||
 Line 39:
-|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Kamitani_2005.pdf|Decoding the visual and subjective contents of the human brain]]|| || ||
+|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Kamitani_2005.pdf|Decoding the visual and subjective contents of the human brain]]||Alexander Muschalle  || Felix Bießmann ||
|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Quiroga2005.pdf|Invariant visual representation by single neurons in the human brain.]]||||