Gunnar Rätsch

According to our database1, Gunnar Rätsch authored at least 105 papers between 1997 and 2019.

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Bibliography

2019
Dynamic compression schemes for graph coloring.
Bioinformatics, 2019

Sparse Binary Relation Representations for Genome Graph Annotation.
Proceedings of the Research in Computational Molecular Biology, 2019

2018
Boosting Black Box Variational Inference.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Predicting circulatory system deterioration in intensive care unit patients.
Proceedings of the First Joint Workshop on AI in Health organized as part of the Federated AI Meeting (FAIM 2018), 2018

On Matching Pursuit and Coordinate Descent.
Proceedings of the 35th International Conference on Machine Learning, 2018

Clustering Meets Implicit Generative Models.
Proceedings of the 6th International Conference on Learning Representations, 2018

A Machine Learning-based Early Warning System for Circulatory System Deterioration in Intensive Care Unit Patients.
Proceedings of the AMIA 2018, 2018

Boosting Variational Inference: an Optimization Perspective.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
RiboDiff: detecting changes of mRNA translation efficiency from ribosome footprints.
Bioinformatics, 2017

Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning Unitary Operators with Help From u(n).
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
When crowds hold privileges: Bayesian unsupervised representation learning with oracle constraints.
Proceedings of the 4th International Conference on Learning Representations, 2016

Efficient privacy-preserving string search and an application in genomics.
Bioinformatics, 2016

SplAdder: identification, quantification and testing of alternative splicing events from RNA-Seq data.
Bioinformatics, 2016

MMR: a tool for read multi-mapper resolution.
Bioinformatics, 2016

A Generative Model of Words and Relationships from Multiple Sources.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Probabilistic clustering of time-evolving distance data.
Machine Learning, 2015

Machine Learning with Interdependent and Non-identically Distributed Data (Dagstuhl Seminar 15152).
Dagstuhl Reports, 2015

Protein translational control and its contribution to oncogenesis revealed by computational methods.
BMC Bioinformatics, 2015

Integrative Genome-wide Analysis of the Determinants of RNA Splicing in Kidney Renal Clear Cell Carcinoma.
Proceedings of the Biocomputing 2015: Proceedings of the Pacific Symposium, 2015

Session Introduction.
Proceedings of the Biocomputing 2015: Proceedings of the Pacific Symposium, 2015

Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014
Regularization-Based Multitask Learning With Applications to Genome Biology and Biological Imaging.
KI, 2014

Oqtans: a multifunctional workbench for RNA-seq data analysis.
BMC Bioinformatics, 2014

Oqtans: the RNA-seq workbench in the cloud for complete and reproducible quantitative transcriptome analysis.
Bioinformatics, 2014

Session Introduction.
Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

2013
Ecological Modeling from Time-Series Inference: Insight into Dynamics and Stability of Intestinal Microbiota.
PLoS Computational Biology, 2013

MITIE: Simultaneous RNA-Seq-based transcript identification and quantification in multiple samples.
Bioinformatics, 2013

An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Multi-task Learning for Computational Biology: Overview and Outlook.
Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012
Multitask Learning in Computational Biology.
Proceedings of the Unsupervised and Transfer Learning, 2012

Efficient Training of Graph-Regularized Multitask SVMs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

2011
Oqtans: a Galaxy-integrated workflow for quantitative transcriptome analysis from NGS Data.
BMC Bioinformatics, 2011

Support vector machines-based identification of alternative splicing in Arabidopsis thaliana from whole-genome tiling arrays.
BMC Bioinformatics, 2011

Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
rQuant.web: a tool for RNA-Seq-based transcript quantitation.
Nucleic Acids Research, 2010

The SHOGUN Machine Learning Toolbox.
Journal of Machine Learning Research, 2010

Inferring latent task structure for Multitask Learning by Multiple Kernel Learning.
BMC Bioinformatics, 2010

Exploiting physico-chemical properties in string kernels.
BMC Bioinformatics, 2010

Next generation genome annotation with mGene.ngs.
BMC Bioinformatics, 2010

Leveraging Sequence Classification by Taxonomy-Based Multitask Learning.
Proceedings of the Research in Computational Molecular Biology, 2010

Novel Machine Learning Methods for MHC Class I Binding Prediction.
Proceedings of the Pattern Recognition in Bioinformatics, 2010

2009
Prototype Classification: Insights from Machine Learning.
Neural Computation, 2009

mGene.web: a web service for accurate computational gene finding.
Nucleic Acids Research, 2009

Transcript quantification with RNA-Seq data.
BMC Bioinformatics, 2009

The Feature Importance Ranking Measure.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

2008
Support Vector Machines and Kernels for Computational Biology.
PLoS Computational Biology, 2008

Revealing sequence variation patterns in rice with machine learning methods.
BMC Bioinformatics, 2008

Transcript Normalization and Segmentation of Tiling Array Data.
Proceedings of the Biocomputing 2008, 2008

An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

POIMs: positional oligomer importance matrices - understanding support vector machine-based signal detectors.
Proceedings of the Proceedings 16th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2008

KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences.
Proceedings of the German Conference on Bioinformatics, 2008

Optimal spliced alignments of short sequence reads.
Proceedings of the ECCB'08 Proceedings, 2008

2007
Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning.
PLoS Computational Biology, 2007

The Need for Open Source Software in Machine Learning.
Journal of Machine Learning Research, 2007

Accurate splice site prediction using support vector machines.
BMC Bioinformatics, 2007

NIPS workshop on New Problems and Methods in Computational Biology.
BMC Bioinformatics, 2007

PALMA: mRNA to genome alignments using large margin algorithms.
Bioinformatics, 2007

Boosting Algorithms for Maximizing the Soft Margin.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Large Scale Multiple Kernel Learning.
Journal of Machine Learning Research, 2006

Learning Interpretable SVMs for Biological Sequence Classification.
BMC Bioinformatics, 2006

Large Scale Hidden Semi-Markov SVMs.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

ARTS: accurate recognition of transcription starts in human.
Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Totally corrective boosting algorithms that maximize the margin.
Proceedings of the Machine Learning, 2006

PALMA: Perfect Alignments using Large Margin Algorithms.
Proceedings of the German Conference on Bioinformatics GCB 2006, 19.09. 2006, 2006

Graph Based Semi-supervised Learning with Sharper Edges.
Proceedings of the Machine Learning: ECML 2006, 2006

The Solution of Semi-Infinite Linear Programs Using Boosting-Like Methods.
Proceedings of the Discovery Science, 9th International Conference, 2006

Solving Semi-infinite Linear Programs Using Boosting-Like Methods.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005
Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection.
Journal of Machine Learning Research, 2005

Efficient Margin Maximizing with Boosting.
Journal of Machine Learning Research, 2005

Classifying 'Drug-likeness' with Kernel-Based Learning Methods.
Journal of Chemical Information and Modeling, 2005

Learning Interpretable SVMs for Biological Sequence Classification.
Proceedings of the Research in Computational Molecular Biology, 2005

A General and Efficient Multiple Kernel Learning Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

RASE: recognition of alternatively spliced exons in C.elegans.
Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

Large scale genomic sequence SVM classifiers.
Proceedings of the Machine Learning, 2005

2004
Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces.
IEEE Trans. Pattern Anal. Mach. Intell., 2003

Active Learning with Support Vector Machines in the Drug Discovery Process.
Journal of Chemical Information and Computer Sciences, 2003

Image Reconstruction by Linear Programming.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Robust multi-class boosting.
Proceedings of the 8th European Conference on Speech Communication and Technology, EUROSPEECH 2003, 2003

2002
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces.
Machine Learning, 2002

Adapting Codes and Embeddings for Polychotomies.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

An Introduction to Boosting and Leveraging.
Proceedings of the Advanced Lectures on Machine Learning, 2002

New Methods for Splice Site Recognition.
Proceedings of the Artificial Neural Networks, 2002

Maximizing the Margin with Boosting.
Proceedings of the Computational Learning Theory, 2002

2001
An introduction to kernel-based learning algorithms.
IEEE Trans. Neural Networks, 2001

Soft Margins for AdaBoost.
Machine Learning, 2001

Active Learning in the Drug Discovery Process.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

A New Discriminative Kernel From Probabilistic Models.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

On the Convergence of Leveraging.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers.
Proceedings of the Artificial Neural Networks, 2001

Robustes Boosting durch konvexe Optimierung.
Proceedings of the Ausgezeichnete Informatikdissertationen 2001, 2001

2000
Engineering support vector machine kernels that recognize translation initiation sites.
Bioinformatics, 2000

Robust Ensemble Learning for Data Mining.
Proceedings of the Knowledge Discovery and Data Mining, 2000

A Mathematical Programming Approach to the Kernel Fisher Algorithm.
Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Barrier Boosting.
Proceedings of the Thirteenth Annual Conference on Computational Learning Theory (COLT 2000), June 28, 2000

1999
Input space versus feature space in kernel-based methods.
IEEE Trans. Neural Networks, 1999

v-Arc: Ensemble Learning in the Presence of Outliers.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Invariant Feature Extraction and Classification in Kernel Spaces.
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites.
German Conference on Bioinformatics, 1999

1998
Regularizing AdaBoost.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

Kernel PCA and De-Noising in Feature Spaces.
Proceedings of the Advances in Neural Information Processing Systems 11, [NIPS Conference, Denver, Colorado, USA, November 30, 1998

An Improvement of AdaBoost to Avoid Overfitting.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

1997
Predicting Time Series with Support Vector Machines.
Proceedings of the Artificial Neural Networks, 1997


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