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|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Oja1982.pdf|A simplified neuron model as a principal component analyzer]] || Tongxin Son || [[mailto:Duncan Blythe duncan.blythe@bccn-berlin.de|Duncan Blythe]] || || [[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 ||
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|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Turk1991.pdf|Eigenfaces for Recognition]]|| Min Zheng|| [[wojciech.samek@campus.tu-berlin.de|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 || [[mailto:Duncan Blythe duncan.blythe@bccn-berlin.de|Duncan Blythe]] ||
|| [[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 ||
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|| [[http://www.user.tu-berlin.de/felix.biessmann/downloads/AKA/Mika1998.pdf|Kernel PCA and De--Noising in Feature Spaces]]|| Sha Huang|| [[bettina.mieth@tu-berlin.de|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||
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|| [[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@campus.tu-berlin.de|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@tu-berlin.de|Felix Bießmann]] ||
|| [[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||

Anwendungen Kognitiver Algorithmen

Blockseminar

Termine und Dozenten

Termin:

Präsentationen 04.07.2012, 10:00 - 13:00

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

Support vector machines for spam categorization

Chengbing Liu

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

IDA Wiki: Main/SS12_AKA (last edited 2012-05-09 16:27:43 by FelixBiessmann)