Gunnar Rätsch

Stephan Mandt

CoRR, 2019

Disentangling Factors of Variation Using Few Labels.

[BibT_eX]

[DOI]

CoRR, 2019

Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies.

[BibT_eX]

[DOI]

Stefan G. Stark

Melanie Fernandes Pradier

CoRR, 2019

Machine learning for early prediction of circulatory failure in the intensive care unit.

[BibT_eX]

[DOI]

CoRR, 2019

Deep Mean Functions for Meta-Learning in Gaussian Processes.

[BibT_eX]

[DOI]

Vincent Fortuin

CoRR, 2019

Dynamic compression schemes for graph coloring.

[BibT_eX]

[DOI]

Bioinform., 2019

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

SOM-VAE: Interpretable Discrete Representation Learning on Time Series.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Improving Clinical Predictions through Unsupervised Time Series Representation Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Scalable Gaussian Processes on Discrete Domains.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series.

[BibT_eX]

[DOI]

CoRR, 2018

Revisiting First-Order Convex Optimization Over Linear Spaces.

[BibT_eX]

[DOI]

Francesco Locatello

Anant Raj

Sai Praneeth Karimireddy

CoRR, 2018

Boosting Black Box Variational Inference.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Francesco Locatello

Anant Raj

Sai Praneeth Karimireddy

Proceedings of the 35th International Conference on Machine Learning, 2018

Clustering Meets Implicit Generative Models.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2018, 2018

Boosting Variational Inference: an Optimization Perspective.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs.

[BibT_eX]

[DOI]

Cristóbal Esteban

CoRR, 2017

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

[BibT_eX]

[DOI]

Bioinform., 2017

Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees.

[BibT_eX]

[DOI]

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).

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

When crowds hold privileges: Bayesian unsupervised representation learning with oracle constraints.

[BibT_eX]

[DOI]

Theofanis Karaletsos

Serge J. Belongie

Proceedings of the 4th International Conference on Learning Representations, 2016

Knowledge Transfer with Medical Language Embeddings.

[BibT_eX]

[DOI]

Theofanis Karaletsos

CoRR, 2016

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

[BibT_eX]

[DOI]

Kana Shimizu

Koji Nuida

Bioinform., 2016

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

[BibT_eX]

[DOI]

Bioinform., 2016

MMR: a tool for read multi-mapper resolution.

[BibT_eX]

[DOI]

André Kahles

Bioinform., 2016

A Generative Model of Words and Relationships from Multiple Sources.

[BibT_eX]

[DOI]

Theofanis Karaletsos

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Probabilistic clustering of time-evolving distance data.

[BibT_eX]

[DOI]

Mach. Learn., 2015

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

[BibT_eX]

[DOI]

Dagstuhl Reports, 2015

Framework for Multi-task Multiple Kernel Learning and Applications in Genome Analysis.

[BibT_eX]

[DOI]

CoRR, 2015

Protein translational control and its contribution to oncogenesis revealed by computational methods.

[BibT_eX]

[DOI]

BMC Bioinform., 2015

Integrative Genome-wide Analysis of the Determinants of RNA Splicing in Kidney Renal Clear Cell Carcinoma.

[BibT_eX]

[DOI]

Proceedings of the Biocomputing 2015: Proceedings of the Pacific Symposium, 2015

Session Introduction.

[BibT_eX]

[DOI]

Søren Brunak

Francisco M. de la Vega

Proceedings of the Biocomputing 2015: Proceedings of the Pacific Symposium, 2015

Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014

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

[BibT_eX]

[DOI]

Künstliche Intell., 2014

Oqtans: a multifunctional workbench for RNA-seq data analysis.

[BibT_eX]

[DOI]

Vipin T. Sreedharan

BMC Bioinform., 2014

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

[BibT_eX]

[DOI]

Vipin T. Sreedharan

Bioinform., 2014

Session Introduction.

[BibT_eX]

[DOI]

Søren Brunak

Francisco M. de la Vega

Joshua M. Stuart

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.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2013

GRED: Graph-Regularized 3D Shape Reconstruction from Highly Anisotropic and Noisy Images.

[BibT_eX]

[DOI]

CoRR, 2013

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

[BibT_eX]

[DOI]

Bioinform., 2013

An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes.

[BibT_eX]

[DOI]

Katherine Redfield Chan

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Multi-task Learning for Computational Biology: Overview and Outlook.

[BibT_eX]

[DOI]

Christian Widmer

Marius Kloft

Proceedings of the Empirical Inference - Festschrift in Honor of Vladimir N. Vapnik, 2013

2012

Multitask Learning in Computational Biology.

[BibT_eX]

[DOI]

Christian Widmer

Proceedings of the Unsupervised and Transfer Learning, 2012

Efficient Training of Graph-Regularized Multitask SVMs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

2011

Oqtans: a Galaxy-integrated workflow for quantitative transcriptome analysis from NGS Data.

[BibT_eX]

[DOI]

BMC Bioinform., 2011

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

[BibT_eX]

[DOI]

BMC Bioinform., 2011

Hierarchical Multitask Structured Output Learning for Large-scale Sequence Segmentation.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Regina Bohnert

Nucleic Acids Res., 2010

The SHOGUN Machine Learning Toolbox.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2010

Inferring latent task structure for Multitask Learning by Multiple Kernel Learning.

[BibT_eX]

[DOI]

BMC Bioinform., 2010

Exploiting physico-chemical properties in string kernels.

[BibT_eX]

[DOI]

BMC Bioinform., 2010

Next generation genome annotation with mGene.ngs.

[BibT_eX]

[DOI]

Regina Bohnert

Georg Zeller

Lisa Hartmann

BMC Bioinform., 2010

Leveraging Sequence Classification by Taxonomy-Based Multitask Learning.

[BibT_eX]

[DOI]

Proceedings of the Research in Computational Molecular Biology, 2010

Novel Machine Learning Methods for MHC Class I Binding Prediction.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition in Bioinformatics, 2010

2009

Prototype Classification: Insights from Machine Learning.

[BibT_eX]

[DOI]

Neural Comput., 2009

mGene.web: a web service for accurate computational gene finding.

[BibT_eX]

[DOI]

Nucleic Acids Res., 2009

KIRMES: kernel-based identification of regulatory modules in euchromatic sequences.

[BibT_eX]

[DOI]

BMC Bioinform., 2009

Transcript quantification with RNA-Seq data.

[BibT_eX]

[DOI]

Regina Bohnert

BMC Bioinform., 2009

The Feature Importance Ranking Measure.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

2008

Support Vector Machines and Kernels for Computational Biology.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2008

Optimal spliced alignments of short sequence reads.

[BibT_eX]

[DOI]

Fabio De Bona

Stephan Ossowski

Korbinian Schneeberger

BMC Bioinform., 2008

Revealing sequence variation patterns in rice with machine learning methods.

[BibT_eX]

[DOI]

Richard M. Bruskiewich

BMC Bioinform., 2008

Transcript Normalization and Segmentation of Tiling Array Data.

[BibT_eX]

[DOI]

Proceedings of the Biocomputing 2008, 2008

An Empirical Analysis of Domain Adaptation Algorithms for Genomic Sequence Analysis.

[BibT_eX]

[DOI]

Christian Widmer

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

POIMs: positional oligomer importance matrices - understanding support vector machine-based signal detectors.

[BibT_eX]

[DOI]

Proceedings of the Proceedings 16th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2008

2007

Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2007

The Need for Open Source Software in Machine Learning.

[BibT_eX]

[DOI]

Carl Edward Rasmussen

J. Mach. Learn. Res., 2007

Accurate splice site prediction using support vector machines.

[BibT_eX]

[DOI]

Petra Philips

BMC Bioinform., 2007

NIPS workshop on New Problems and Methods in Computational Biology.

[BibT_eX]

[DOI]

Gal Chechik

Christina S. Leslie

William Stafford Noble

Quaid Morris

BMC Bioinform., 2007

PALMA: mRNA to genome alignments using large margin algorithms.

[BibT_eX]

[DOI]

Bioinform., 2007

Boosting Algorithms for Maximizing the Soft Margin.

[BibT_eX]

[DOI]

Karen A. Glocer

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006

Large Scale Multiple Kernel Learning.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2006

Learning Interpretable SVMs for Biological Sequence Classification.

[BibT_eX]

[DOI]

Christin Schäfer

BMC Bioinform., 2006

Large Scale Hidden Semi-Markov SVMs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

ARTS: accurate recognition of transcription starts in human.

[BibT_eX]

[DOI]

Alexander Zien

Proceedings of the Proceedings 14th International Conference on Intelligent Systems for Molecular Biology 2006, 2006

Totally corrective boosting algorithms that maximize the margin.

[BibT_eX]

[DOI]

Jun Liao

Proceedings of the Machine Learning, 2006

PALMA: Perfect Alignments using Large Margin Algorithms.

[BibT_eX]

[DOI]

Proceedings of the German Conference on Bioinformatics GCB 2006, 19.09. 2006, 2006

Graph Based Semi-supervised Learning with Sharper Edges.

[BibT_eX]

[DOI]

Hyunjung Shin

N. Jeremy Hill

Proceedings of the Machine Learning: ECML 2006, 2006

The Solution of Semi-Infinite Linear Programs Using Boosting-Like Methods.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science, 9th International Conference, 2006

Solving Semi-infinite Linear Programs Using Boosting-Like Methods.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

2005

Robust boosting via convex optimization

[BibT_eX]

[DOI]

PhD thesis, 2005

Image reconstruction by linear programming.

[BibT_eX]

[DOI]

IEEE Trans. Image Process., 2005

Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2005

Efficient Margin Maximizing with Boosting.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2005

Classifying 'Drug-likeness' with Kernel-Based Learning Methods.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2005

A General and Efficient Multiple Kernel Learning Algorithm.

[BibT_eX]

[DOI]

Christin Schäfer

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

RASE: recognition of alternatively spliced exons in C.elegans.

[BibT_eX]

[DOI]

Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

Large scale genomic sequence SVM classifiers.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2005

2004

Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2003

Active Learning with Support Vector Machines in the Drug Discovery Process.

[BibT_eX]

[DOI]

J. Chem. Inf. Comput. Sci., 2003

Robust multi-class boosting.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2002

A New Discriminative Kernel from Probabilistic Models.

[BibT_eX]

[DOI]

Neural Comput., 2002

Sparse Regression Ensembles in Infinite and Finite Hypothesis Spaces.

[BibT_eX]

[DOI]

Ayhan Demiriz

Kristin P. Bennett

Mach. Learn., 2002

Adapting Codes and Embeddings for Polychotomies.

[BibT_eX]

[DOI]

Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

An Introduction to Boosting and Leveraging.

[BibT_eX]

[DOI]

Ron Meir

Proceedings of the Advanced Lectures on Machine Learning, 2002

New Methods for Splice Site Recognition.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2002

Maximizing the Margin with Boosting.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory, 2002

2001

An introduction to kernel-based learning algorithms.

[BibT_eX]

[DOI]

IEEE Trans. Neural Networks, 2001

Soft Margins for AdaBoost.

[BibT_eX]

[DOI]

Takashi Onoda

Mach. Learn., 2001

Active Learning in the Drug Discovery Process.

[BibT_eX]

[DOI]

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

On the Convergence of Leveraging.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks, 2001

Robustes Boosting durch konvexe Optimierung.

[BibT_eX]

[DOI]

Proceedings of the Ausgezeichnete Informatikdissertationen 2001, 2001

2000

Engineering support vector machine kernels that recognize translation initiation sites.

[BibT_eX]

[DOI]

Bioinform., 2000

Robust Ensemble Learning for Data Mining.

[BibT_eX]

[DOI]

Proceedings of the Knowledge Discovery and Data Mining, 2000

A Mathematical Programming Approach to the Kernel Fisher Algorithm.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

Barrier Boosting.

[BibT_eX]

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.

[BibT_eX]

[DOI]

Christopher J. C. Burges

IEEE Trans. Neural Networks, 1999

v-Arc: Ensemble Learning in the Presence of Outliers.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

Proceedings of the German Conference on Bioinformatics, 1999

1998

Regularizing AdaBoost.

[BibT_eX]

[DOI]

Takashi Onoda

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

Takashi Onoda