Information Science and Engineering Lab

We perform teaching and research in machine learning strategies for the pattern analysis of various kinds of data. This comprises statistical models for clustering, graphical models for network inference and algorithmic methods to efficiently find these structures in the data.

Contact Info
CAB F 61.1
Universitaetstrasse 6,
8092 Zurich
Schweiz

+41 44 632 64 96

Follow Us

Information Science and Engineering Lab

We perform teaching and research in machine learning strategies for the pattern analysis of various kinds of data. This comprises statistical models for clustering, graphical models for network inference and algorithmic methods to efficiently find these structures in the data.

Contact Info
CAB F 61.1
Universitaetstrasse 6,
8092 Zurich
Schweiz

+41 44 632 64 96

Follow Us

Publications - page 18

Proteome coverage prediction with infinite Markov models

Manfred Claassen, Ruedi Aebersold, Joachim M. Buhmann,

Bioinformatics, 25

DOI: 10.3929/ethz-b-000019118      Research Collection

Protein identification false discovery rates for very large proteomics data sets generated by tandem mass spectrometry

Lukas Reiter, Manfred Claassen, Sabine P. Schrimpf, Marko Jovanovic, Alexander Schmidt, Joachim M. Buhmann, Michael O. Hengartner, Ruedi Aebersold,

Molecular & Cellular Proteomics, 8

Research Collection

Optimized expected information gain for nonlinear dynamical systems

Alberto Giovanni Busetto, Cheng Soon Ong, Joachim M. Buhmann,

26th Annual International Conference on Machine Learning, 382

Research Collection

Multi-assignment clustering for Boolean data-2009

Andreas P. Streich, Mario Frank, David Basin, Joachim M. Buhmann,

26th Annual International Conference on Machine Learning 2009 (ICML'09), 382

Research Collection

Manifold Regularization for Semi-Supervised Sequential Learning

Yvonne Moh, Joachim M. Buhmann,

34th IEEE International Conference on Acoustics, Speech and Signal Processing 2009 (ICASSP 2009),

Research Collection

Inter-active learning of randomized tree ensembles for object detection

Thomas J. Fuchs, Joachim M. Buhmann,

12th International Conference on Computer Vision workshops (ICCV workshops 2009),

Research Collection

Ignoring Co-Occurring Sources in Learning from Multi-Labeled Data Leads to Model Mismatch

Andreas P. Streich, Joachim M. Buhmann,

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2009,

Research Collection

Graph-Based Pancreatic Islet Segmentation for Early Type 2 Diabetes Mellitus on Histopathological Tissue

Xenofon Floros, Thomas J. Fuchs, Markus P. Rechsteiner, Giatgen Spinas, Holger Moch, Joachim M. Buhmann,

12th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2009), 5762

Research Collection

Detection of Urothelial Bladder Cancer Cells in Voided Urine Can Be Improved by a Combination of Cytology and Standardized Microsatellite Analysis

Peter J. Wild, Thomas J. Fuchs, Robert Stoeh, Dieter Zimmermann, Simona Frigerio, Barbara Padberg, Inbal Steiner, Ellen C. Zwarthoff, Maximilian Burger, Stefan Denzinger, Ferdinand Hofstaedter, Glen Kristiansen, Thomas Hermanns, Hans-Helge Seifert, Maurizio Provenzano, Tullio Sulser, Volker Roth, Joachim M. Buhmann, Holger Moch, Arndt Hartmann,

Cancer Epidemiology, Biomarkers and Prevention, 18

Research Collection

Adaptive bandwidth selection for biomarker discovery in mass spectrometry

Bernd Fischer, Volker Roth, Joachim M. Buhmann,

Artificial intelligence in medicine, 45

Research Collection