The 2009 European Workshop on Challenges in Modern Massive Data Sets (EMMDS 2009) will address algorithmic, mathematical, and statistical challenges in modern large-scale data analysis. The goals of EMMDS 2009 are to explore novel techniques for modelling and analyzing massive, high-dimensional, and nonlinearly-structured scientific and internet data sets, and to bring together computer scientists, statisticians, mathematicians, and data analysis practitioners to promote cross-fertilization of ideas. Several areas that will be discussed in detail include:
For information on previous MMDS meetings see http://mmds.stanford.edu.
Time | Talk |
---|---|
09:10 - 10:10 | Jerome Friedman Predictive learning via rule ensembles |
10:30 - 11:15 | Yee Whye Teh Bayesian nonparametrics in document and language modeling |
11:15 - 12:00 | Ole Winther Hierarchical bayesian modelling for collaborative filtering |
13:30 - 14:30 | Bernhard Schölkopf Machine learning with positive definite kernels |
14:30 - 15:05 | Klaus Mosegaard Metaheuristics in science and engineering |
15:25 - 16:00 | Nello Cristianini Looking for memes in media content |
16:00 - 16:35 | Mikkel Schmidt Bayesian matrix factorization approaches to blind source separation |
Time | Talk |
---|---|
09:00 - 10:00 | Edward Chang Parallel algorithms for collaborative filtering |
10:20 - 10:55 | Rasmus Bro Applications of tensor methods in life sciences data |
10:55 - 11:30 | Pierre Comon Tensor decompositions in statistical signal processing |
11:30 - 12:05 | Lieven De Lathauwer Tucker compression, Parallel Factor Analysis and block term decompositions: New results |
12:05 - 12:40 | Lars Eldén Krylov methods for tensors |
14:00 - 15:00 | Tomaso Poggio From neuroscience to hierarchical learning architectures |
15:00 - 17:45 | Poster Session |
Time | Talk |
---|---|
09:00 - 10:00 | Ricardo Baeza-Yates The power of data |
10:20 - 11:20 | Scott Makeig Multiscale brain/body imaging: Towards a single brain electrophysiology |
11:25 - 12:00 | John Ashburner Brain morphometrics from MRI scans data |
13:30 - 14:30 | Joachim Buhmann Structure validation in clustering by stability analysis |
14:30 - 15:05 | Charles Elkan Accounting for burstiness in topic models |
15:25 - 16:00 | Neil Lawrence Nonlinear matrix factorization with gaussian processes |
16:00 - 16:35 | Michael Mahoney Community structure in large social and information networks |
16:35 - 17:10 | Morten Mørup Clustering on the simplex |
Time | Talk |
---|---|
09:00 - 10:00 | Gunnar Carlsson Topology and data |
10:20 - 10:55 | Risi Kondor Non-commutative harmonic analysis in machine learning: the skew spectrum and the graphlet spectrum of graphs |
10:55 - 11:30 | Samuel Kaski Probabilistic retrieval and visualization of relevant experiments |
11:30 - 12:05 | Lek-Heng Lim Principal cumulant components analysis |
13:30 - 14:30 | Pedro Cano Music recommendation systems: A complex networks perspective |
14:30 - 15:05 | Joaquin Quiñonero Candela Probabilistic machine learning in computational advertising |
15:25 - 16:00 | Mark Herbster Resistive geometry for graph-based transduction |
16:00 - 16:35 | Sune Lehmann Connections matter. Communities of links in complex networks |
16:35 - 17:10 | Lars Kai Hansen
Machine learning in complex networks |
John Ashburner | University College London |
Ricardo Baeza-Yates | Yahoo! Research, Barcelona |
Rasmus Bro | University of Copenhagen |
Joachim Buhmann | Swiss Federal Institute of Technology (ETH), Zürich |
Joaquin Quiñonero Candela | Microsoft Research, Cambridge |
Pedro Cano | Barcelona Music and Audio Technologies |
Edward Chang | Google Research, Beijing |
Pierre Comon | University of Nice, Sophia-Antipolis |
Nello Cristianini | University of Bristol |
Lieven De Lathauwer | Katholieke Universiteit Leuven |
Lars Elden | Linköping University |
Charles Elkan | University of California, San Diego |
Jerome Friedman | Stanford University |
Mark Herbster | University College London |
Samuel Kaski | Helsinki University of Technology |
Risi Kondor | University College London / California Institute of Technology |
Neil Lawrence | University of Manchester |
Sune Lehmann | Northeastern University / Harvard University |
Scott Makeig | University of California, San Diego |
Klaus Mosegaard | University of Copenhagen |
Tomaso Poggio | Massachusetts Institute of Technology |
Mikkel Schmidt | University of Cambridge |
Bernhard Schölkopf | Max Planck Institute |
Yee Whye Teh | University College London |
Ole Winther | Technical University of Denmark / University of Copenhagen |
Morten Mørup, Technical University of Denmark
Lek-Heng Lim, University of California, Berkeley
Michael Mahoney, Stanford University
Lars Kai Hansen, Technical University of Denmark
Gunnar Carlsson, Stanford University
Contact: mmds-organizers@imm.dtu.dk