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

Learn More

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

Learn More

Follow Us

Conference Paper - page 7

2012 Conference Paper

The Information Content in Sorting Algorithms

Ludwig M. Busse, Morteza Haghir Chehreghani, Joachim M. Buhmann,

IEEE International Symposium on Information Theory (ISIT) 2012,

Research Collection

2012 Conference Paper

Computational modeling for assessment of IBD: To be or not to be?

Franciscus M. Vos, Jeroen A.W. Tielbeek, Robiel E. Naziroglu, Zhang Li, Peter Schüffler, Dwarikanath Mahapatra, Alexander Wiebel, C. Lavini, Joachim M. Buhmann, Hans-Christian Hege, Jaap Stoker, Lucas van Vliet,

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2012),

Research Collection

2012 Conference Paper

Anisotropic ssTEM Image Segmentation Using Dense Correspondence across Sections

Dmitry Laptev, Alexander Vezhnevets, Sarvesh Dwivedi, Joachim M. Buhmann,

15th International Conference for Medical Image Computing and Computer-Assisted Intervention (MICCAI 2012), 7510

Research Collection

2012 Conference Paper

Active learning for semantic segmentation with expected change

Alexander Vezhnevets, Joachim M. Buhmann, Vittorio Ferrari,

IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2012),

Research Collection

2012 Conference Paper

A Supervised Learning Based Approach to Detect Crohn’s Disease in Abdominal MR Volumes

Dwarikanath Mahapatra, Peter J. Schüffler, J.A.W. Tielbeek, Joachim M. Buhmann, Franciscus M. Vos,

4th International Workshop International Workshop on Computational and Clinical Applications in Abdominal Imaging, Held in Conjunction with MICCAI 2012, 7601

Research Collection

Crohn S Disease Supervised Learning Magnetic Resonance Imaging
2011 Conference Paper

Weakly Supervised Semantic Segmentation with a Multi-image Model

Alexander Vezhnevets, Vittorio Ferrari, Joachim M. Buhmann,

13th International Conference on Computer Vision (ICCV 2011),

Research Collection

2011 Conference Paper

The Minimum Transfer Cost Principle for Model-Order Selection

Mario Frank, Morteza Haghir Chehreghani, Joachim M. Buhmann,

European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD) 2011, 6911

Research Collection

Clustering Generalization Error Transfer Costs Cross Validation
2011 Conference Paper

Selecting the rank of truncated SVD by Maximum Approximation Capacity

Mario Frank, Joachim M. Buhmann,

IEEE International Symposium on Information Theory proceedings (ISIT) 2011,

Research Collection

2011 Conference Paper

Predicting graduate-level performance from undergraduate achievements

Judith Zimmermann, Kay H Brodersen, Jean-Philippe Pellet, Elias August, Joachim M. Buhmann,

4th International Conference on Educational Data Mining (EDM 2011),

Research Collection

2011 Conference Paper

Modeling Engagement Dynamics in Spelling Learning

Gian-Marco Baschera, Alberto Giovanni Busetto, Severin Klingler, Joachim M. Buhmann, Markus Gross,

15th International Conference on Artificial Intelligence in Education (AIED 2011), 6738

Research Collection

Engagement Modeling Feature Processing Domain Knowledge Dynamic Bayesian Network Learning Spelling