Thomas Gärtner

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024

The Expressive Power of Path-Based Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Improving Expert Specialization in Mixture of Experts.

[BibT_eX]

[DOI]

Yamuna Krishnamurthy

Chris Watkins

CoRR, 2023

Expressivity-Preserving GNN Simulation.

[BibT_eX]

[DOI]

Fabian Jogl

Maximilian Thiessen

Magnus W. D. Hanson-Heine

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Expectation-Complete Graph Representations with Homomorphisms.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

2022

Kernel Methods for Predicting Yields of Chemical Reactions.

[BibT_eX]

[DOI]

Alexe L. Haywood

Joseph Redshaw

J. Chem. Inf. Model., 2022

Online Learning of Convex Sets on Graphs.

[BibT_eX]

[DOI]

Maximilian Thiessen

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021

Active Learning of Convex Halfspaces on Graphs.

[BibT_eX]

[DOI]

Maximilian Thiessen

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Interactive Machine Learning with Structured Data.

[BibT_eX]

[DOI]

Proceedings of the Conference "Lernen, 2020

2019

Scalable Learning in Reproducing Kernel Krein Spaces.

[BibT_eX]

[DOI]

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

2018

Corresponding Projections for Orphan Screening.

[BibT_eX]

[DOI]

CoRR, 2018

Large Scale Learning with Kreĭn Kernels.

[BibT_eX]

[DOI]

CoRR, 2018

Learning in Reproducing Kernel Krein Spaces.

[BibT_eX]

[DOI]

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

2017

Graph Kernels.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

Co-Regularised Support Vector Regression.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Effective Parallelisation for Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Nyström Method with Kernel K-means++ Samples as Landmarks.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

Active Search in Intensionally Specified Structured Spaces.

[BibT_eX]

[DOI]

Roman Garnett

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

2016

Guest editors' introduction to the EcmlPkdd 2016 journal track special issue of Machine Learning.

[BibT_eX]

[DOI]

Mach. Learn., 2016

Greedy Feature Construction.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Ligand-Based Virtual Screening with Co-regularised Support Vector Regression.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining Workshops, 2016

2015

Introducing the 'active search' method for iterative virtual screening.

[BibT_eX]

[DOI]

J. Comput. Aided Mol. Des., 2015

2014

Interactive Knowledge-Based Kernel PCA.

[BibT_eX]

[DOI]

Daniel Paurat

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Predicting unexpected influxes of players in EVE online.

[BibT_eX]

[DOI]

Proceedings of the 2014 IEEE Conference on Computational Intelligence and Games, 2014

2013

InVis: A Tool for Interactive Visual Data Analysis.

[BibT_eX]

[DOI]

Daniel Paurat

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Beating Human Analysts in Nowcasting Corporate Earnings by Using Publicly Available Stock Price and Correlation Features.

[BibT_eX]

[DOI]

Michael Kamp

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

2012

Linear space direct pattern sampling using coupling from the past.

[BibT_eX]

[DOI]

Sandy Moens

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Dynamic difficulty for checkers and Chinese chess.

[BibT_eX]

[DOI]

Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012

2011

Predicting Dynamic Difficulty.

[BibT_eX]

[DOI]

Olana Missura

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

Direct Pattern Sampling with Respect to Pattern Frequency.

[BibT_eX]

Proceedings of the Report of the symposium "Lernen, 2011

Direct local pattern sampling by efficient two-step random procedures.

[BibT_eX]

[DOI]

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

A Fixed Parameter Tractable Integer Program for Finding the Maximum Order Preserving Submatrix.

[BibT_eX]

[DOI]

Jens Humrich

Gemma C. Garriga

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

Graph Kernels.

[BibT_eX]

[DOI]

Proceedings of the Encyclopedia of Machine Learning, 2010

Formal Concept Sampling for Counting and Threshold-Free Local Pattern Mining.

[BibT_eX]

[DOI]

Henrik Grosskreutz

Proceedings of the SIAM International Conference on Data Mining, 2010

Counting-based Output Prediction for Orphan Screening.

[BibT_eX]

[DOI]

Katrin Ullrich

Christoph Stahr

Proceedings of the LWA 2010, 2010

On-Line Handwriting Recognition with Parallelized Machine Learning Algorithms.

[BibT_eX]

[DOI]

Sebastian Bothe

Proceedings of the KI 2010: Advances in Artificial Intelligence, 2010

Label Ranking Algorithms: A Survey.

[BibT_eX]

[DOI]

Proceedings of the Preference Learning., 2010

2009

On structured output training: hard cases and an efficient alternative.

[BibT_eX]

[DOI]

Mach. Learn., 2009

Guest editors' introduction: special issue on mining and learning with graphs.

[BibT_eX]

[DOI]

Gemma C. Garriga

Mach. Learn., 2009

Ligand Prediction from Protein Sequence and Small Molecule Information Using Support Vector Machines and Fingerprint Descriptors.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2009

Probabilistic Structured Predictors.

[BibT_eX]

[DOI]

Proceedings of the UAI 2009, 2009

Player Modeling for Intelligent Difficulty Adjustment.

[BibT_eX]

Olana Missura

Proceedings of the LWA 2009: Workshop-Woche: Lernen, 2009

Context-Based Clustering of Image Search Results.

[BibT_eX]

[DOI]

Proceedings of the KI 2009: Advances in Artificial Intelligence, 2009

On the Complexity of Constraint-Based Theory Extraction.

[BibT_eX]

[DOI]

Proceedings of the Discovery Science, 12th International Conference, 2009

2008

Kernels for Structured Data

[BibT_eX]

[DOI]

Series in Machine Perception and Artificial Intelligence 72, WorldScientific, ISBN: 978-981-4471-03-9, 2008

Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds.

[BibT_eX]

[DOI]

J. Chem. Inf. Model., 2008

Towards Engaging Games.

[BibT_eX]

Olana Missura

Kristian Kersting

Proceedings of the LWA 2008, 2008

Regularization path for Ranking SVM.

[BibT_eX]

[DOI]

Karina Zapien Arreola

Gilles Gasso

Stéphane Canu

Proceedings of the 16th European Symposium on Artificial Neural Networks, 2008

2007

Semidefinite Ranking on Graphs.

[BibT_eX]

[DOI]

Proceedings of the Mining and Learning with Graphs, 2007

Efficient Kernel Methods for Graphs.

[BibT_eX]

[DOI]

Proceedings of the Mining and Learning with Graphs, 2007

The Cost of Learning Directed Cuts.

[BibT_eX]

[DOI]

Gemma C. Garriga

Proceedings of the Machine Learning: ECML 2007, 2007

2006

Graph kernels and Gaussian processes for relational reinforcement learning.

[BibT_eX]

[DOI]

Kurt Driessens

Jan Ramon

Mach. Learn., 2006

Simpler knowledge-based support vector machines.

[BibT_eX]

[DOI]

Quoc V. Le

Alexander J. Smola

Proceedings of the Machine Learning, 2006

Efficient co-regularised least squares regression.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, 2006

Transductive Gaussian Process Regression with Automatic Model Selection.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: ECML 2006, 2006

2005

Large-Scale Multiclass Transduction.

[BibT_eX]

[DOI]

S. V. N. Vishwanathan

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

Kernfunktionen für Strukturierte Daten.

[BibT_eX]

[DOI]

Proceedings of the Ausgezeichnete Informatikdissertationen 2005, 2005

Kernels for Predictive Graph Mining.

[BibT_eX]

[DOI]

Proceedings of the From Data and Information Analysis to Knowledge Engineering, 2005

Kernels for structured data.

[BibT_eX]

[DOI]

PhD thesis, 2005

2004

Kernels and Distances for Structured Data.

[BibT_eX]

[DOI]

John W. Lloyd

Mach. Learn., 2004

Cyclic pattern kernels for predictive graph mining.

[BibT_eX]

[DOI]

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Fisher Kernels for Logical Sequences.

[BibT_eX]

[DOI]

Kristian Kersting

Proceedings of the Machine Learning: ECML 2004, 2004

2003

A survey of kernels for structured data.

[BibT_eX]

[DOI]

SIGKDD Explor., 2003

On Graph Kernels: Hardness Results and Efficient Alternatives.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

2002

Kernels for Structured Data.

[BibT_eX]

[DOI]

John W. Lloyd

Proceedings of the Inductive Logic Programming, 12th International Conference, 2002

Multi-Instance Kernels.

[BibT_eX]

Proceedings of the Machine Learning, 2002

2001

WBCsvm: Weighted Bayesian Classification based on Support Vector Machines.

[BibT_eX]