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19 Οκτ 2013 (πριν από 3 χρόνια και 5 μήνες)

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Information Retrieval in High Dimensional Data

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Information Retrieval in High
Dimensional Data


Wintersemester 2011213


Prof. Dr. M. Kleinsteuber and Dipl. Math. M. Seibert,

Geometric Optimization and Machine Learning Group,

TU München

A test: Find this person in the audience:

Information Retrieval in High Dimensional Data

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How do we extract/store the picture‘s information?

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Information Retrieval in High Dimensional Data

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Where would you go for a 12 months stay? Analyze the following data:

Dataset 1

Information Retrieval in High Dimensional Data

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Where to go for a 12months stay? Analyze the following data:

Dataset 2

Information Retrieval in High Dimensional Data

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Where to go for a 12months stay? Analyze the following data:

Dataset 3

Information Retrieval in High Dimensional Data

Dataset 1 (Porto)

Dataset 2 (Honululu)

Dataset 3 (Canberra)



How do we extract information?

Is it possible to divide simply into „good“ and „bad“ climate?

Is it possible to visualize climate
-
relatedness of cities?

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Information Retrieval in High Dimensional Data

More examples

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Information Retrieval in High Dimensional Data

Speech Recognition

Text Classification

Image Analysis


Recognize digits/faces

Sound Separation

Data Visualization

In this course:

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Information Retrieval in High Dimensional Data

No Support Vector Machines

No Regression

No Factor Analysis

No Random Projection

No Neural Networks

No Hidden Markov Models

No Bayes Classifier

No Self Organizing Maps

.....

Reference: I. Fodor: A survey of dimension reduction techniques,

Technical Report, Berkeley 2002.

Get in touch with some of the tools!

INSTEAD: Outline of the course:

1.
Curse of Dimensionality

2.
Statistical Decision Making

3.
Principal Component Analysis

4.
Linear Discriminant Analysis

5.
Independent Component Analysis

6.
Multidimensional Scaling

7.
Isomap vs. Local Linear Embedding

8.
Christmas

9.
Kernel PCA

10.
Robust PCA

11.
Sparsity and Morphological Component Analysis

Computer Vision


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Literature:

J. Izenman. Modern Multivariate Statistical Techniques.
Springer 2008.

J.A. Lee, M. Verleysen: Nonlinear Dimensionality Reduction,
Springer 2007.

T. Hastie, R. Tibshirani, J. Friedman. The elements of
statistical Learning, Springer 2009.

Papers (will be provided when appropriate)

Information Retrieval in High Dimensional Data

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Data Analysis

Books/Papers/Internet...

mk

Studis

Communicate

Contents

Give

feedback/Ask

questions

Studis

mk



Accept Methods



Be interested



Be independent



Ask questions



Give feedback



Choose methods



Choose topics



Address the questions



Accept Feedback

Structure of Course

Information Retrieval in High Dimensional Data

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Lecture 2 + Tutorials 2 (M. Seibert and I) (4 assignments+1
Poster Session)

LABCOURSE (Matlab Programming/Discussion and reading
group/Postersession/etc.) 3

Examination:

assignments required (max. 5 x 20 pts) 33%

30 mins oral examination 66%

(up to two persons per exam)

Questions?

Information Retrieval in High Dimensional Data

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