2nd Workshop on Applications of Pattern Analysis (WAPA), Castro Urdiales 2011

2nd Workshop on Applications of Pattern Analysis (WAPA), Castro Urdiales 2011

17 Lectures · Oct 19, 2011

About

Pattern Analysis and Statistical Learning cover a wide range of technologies and theoretical frameworks, and significant activity in the past years has resulted in a remarkable convergence and many advances in the theory and principles underlying the field.

Bringing these technologies to real world demanding applications is however often treated as a separate problem, one that does not directly affect the field as a whole. It is instead important to consider the field of Pattern Analysis as fully including all issues involved with the applications of this technology, and hence all issues that arise when deploying, scaling, implementing and using the technology.

We call for constributions in the form of Demos, Case Studies, Working Systems, Real World Applications and Usage Scenarios. Challenges may stem from the violation of common theoretical assumptions, from the specific types of patterns and noise arising in certain scenarios, or from the problem of scaling up the implementation of state of the art algorithms to real world sizes, or from the creation of integrated software systems that contain multiple pattern-analysis components.

We are also interested in new application areas, where Pattern Analysis has been deployed with success, and in issues involving the visualisation and delivery and exploitation of the patterns discovered by PA technologies. Systems working in noisy and unstructured environments and situations are particularly interesting.

The goal is to discuss and reward work aimed at making theory useful and relevant, without requesting the researchers to propose new theoretical methods, but rather requesting to show how they solved the many challenges related to applying these methods to real world scenarios, or how they benefited other fields of research. Getting ideas to work in real scenarios is what this is about.

More information can be found at WAPA 2011.

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Uploaded videos:

Opening

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05:55

Opening

José L. Balcázar

Nov 11, 2011

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2549 Views

Opening

Invited Talks

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59:11

Utilizing Unlabeled Data for Classification-Prediction Learning

Shai Ben-David

Nov 11, 2011

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3738 Views

Invited Talk
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01:10:21

Medical Text Mining

Tom Diethe

Nov 11, 2011

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4935 Views

Invited Talk

Open Text Analysis

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33:52

Detecting Sentiment Change in Twitter Streaming Data

Albert Bifet

Nov 11, 2011

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6243 Views

Lecture
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20:13

Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classific...

Manuel Baena-Garcia

Nov 11, 2011

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3091 Views

Lecture

Classification

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32:32

Streaming Multi-label Classification

Jesse Read

Nov 11, 2011

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6115 Views

Lecture
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30:02

Comparing classification methods for predicting distance students' performance

Diego Garcia-Saiz

Nov 11, 2011

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4386 Views

Lecture

Images and Vision

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15:46

Employing The Complete Face in AVSR to Recover from Facial Occlusions

Ben Hall

Nov 11, 2011

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2903 Views

Lecture
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56:25

Bayesian Probabilistic Models for Image Retrieval

Vassilios Stathopoulos

Nov 11, 2011

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3372 Views

Lecture

Harvest

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06:57

The Pascal-2 Harvest Programme

José L. Balcázar

Nov 11, 2011

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2922 Views

Introduction
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39:14

Introduction to KNIME

Tobias Kötter

Nov 11, 2011

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6840 Views

Lecture
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54:45

The "yacaree" approach to association rules

José L. Balcázar

Nov 11, 2011

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3083 Views

Lecture
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34:22

Self-Tuning Association Rules for KNIME

Javier de la Dehesa

Nov 11, 2011

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3969 Views

Lecture
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45:10

Treeler: Open-source Structured Prediction for NLP

Xavier Carreras

Nov 11, 2011

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5094 Views

Lecture

Change Tracking

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22:12

MOA Concept Drift Active Learning Strategies for Streaming Data

Albert Bifet

Nov 11, 2011

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5984 Views

Lecture
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42:33

A Software System for the Microbial Source Tracking Problem

David Sànchez

Nov 11, 2011

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3075 Views

Lecture
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27:14

Automating Quantitative Narrative Analysis of News Data

Saatviga Sudhahar

Nov 11, 2011

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9296 Views

Lecture