European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Antwerp 2008

About

The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) will be located in Antwerp, Belgium, from September 15th to 19th, 2008. This event builds upon a very successful series of 18 ECML and 11 PKDD conferences, which have been jointly organized for the past seven years. It has become the major European scientific event in these fields and in 2008 it will comprise presentations of contributed papers and invited speakers, a wide program of workshops and tutorials, a discovery challenge, a demo track and an industrial track.

Videos

Tutorials

02:23:21

Data Mining for Anomaly Detection

Aleksandar Lazarevic,

Jaideep Srivastava,

Varun Chandola,

Vipin Kumar,

Arindam Banerjee

Oct 10, 2008

31325 views

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Antwerp 2008

About

Videos

Tutorials

Data Mining for Anomaly Detection

Aleksandar Lazarevic,

Jaideep Srivastava,

Varun Chandola,

Vipin Kumar,

Arindam Banerjee

Embedded Machine Learning: Using Support Vector Machines in Wireless Sensor Netw...

Rasmus Pedersen

The Regularization Frontier in Machine Learning

Gilles Gasso

Knowledge Discovery from Evolving Data

Frank Hoppner,

Mirko Böttcher,

Myra Spiliopoulou

Opening and Awards

Ecml/Pkdd 2008 Opening and Awards Ceremony

Invited Talks

Learning language from its perceptual context

Raymond J. Mooney

From Microscopy Images to Models of Cellular Processes

Yoav Freund

Data Clustering: 50 Years Beyond K-means

Anil K. Jain

Industrial data mining, Challenges and perspectives

Françoise Fogelman Soulié

The role of hierarchies in exploratory data mining

Raghu Ramakrishnan

Support Vector Machines

Exact and Approximate Inference for Annotating Graphs with Structural SVMs

Tobias Scheffer,

Thoralf Klein,

Ulf Brefeld

Sequence Labelling SVMs Trained in One Pass

Léon Bottou,

Nicolas Usunier,

Antoine Bordes

Cascade RSVM in Peer-to-Peer Networks

Hock Hee Ang,

Wee Keong Ng,

Vivekanand Gopalkrishnan,

Steven C. H. Hoi

Improving Classification with Pairwise Constraints: A Margin-based Approach

Nam Nguyen,

Rich Caruana

A Fast Method for Training Linear SVM in the Primal

Thierry Artières,

Trinh Minh Tri Do

Matrix Factorization

Learning Bidirectional Similarity for Collaborative Filtering

Qiang Yang,

Jianmin Wu,

Bin Cao,

Jian Tao Sun,

Zheng Chen

Improving Maximum Margin Matrix Factorization

Alexandros Karatzoglou,

Alex Smola,

Markus Weimer

A Unified View of Matrix Factorization Models

Ajit Singh,

Geoffrey J. Gordon

The Boolean Column and Column-Row Matrix Decompositions

Pauli Miettinen

Discovery

Multiple Manifold Learning Framework based on Hierarchical Mixture Density Model

Mark A. Fardal,

Peter Tino,

Xiaoxia Wang

Exceptional Model Mining

Arno Knobbe,

Ad Feelders,

Dennis Leman

Mining Edge-Weighted Call Graphs to Localise Software Bugs

Frank Eichinger

Tight Optimistic Estimates for Fast Subgroup Discovery

Henrik Grosskreutz,