Thomas Gärtner

发表

Graph kernels and Gaussian processes for relational reinforcement learning

Thomas Gärtner, Kurt Driessens, Jan Ramon, 2006, Machine-mediated learning.

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

Thomas Gärtner, Stefan Wrobel, Martin Vogt, 2016, 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW).

Effective Parallelisation for Machine Learning

Thomas Gärtner, Michael Kamp, Mario Boley, 2017, NIPS.

Simulation of Product Change Effects on the Duration of Development Processes Based on the DSM

Thomas Gärtner, Christopher M. Schlick, N. Rohleder, 2008 .

Large-Scale Multiclass Transduction

Thomas Gärtner, Alexander J. Smola, Quoc V. Le, 2005, NIPS.

On the Complexity of Constraint-Based Theory Extraction

Thomas Gärtner, Mario Boley, Mario Boley, 2009, Discovery Science.

Predicting Dynamic Difficulty

Thomas Gärtner, Olana Missura, Olana Missura, 2011, NIPS.

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

Thomas Gärtner, Hanna Geppert, Stefan Wrobel, 2008, J. Chem. Inf. Model..

Probabilistic Structured Predictors

Thomas Gärtner, Shankar Vembu, Mario Boley, 2009, UAI.

Direct local pattern sampling by efficient two-step random procedures

Daniel Paurat, Thomas Gärtner, Claudio Lucchese, 2011, KDD.

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

Thomas Gärtner, Gemma C. Garriga, 2009, Machine Learning.

Label Ranking Algorithms: A Survey

Thomas Gärtner, Shankar Vembu, Shankar Vembu, 2010, Preference Learning.

Learning in Reproducing Kernel Krein Spaces

Thomas Gärtner, Dino Oglic, Dino Oglic, 2018, ICML.

Kernfunktionen für Strukturierte Daten

Thomas Gärtner, 2005, Ausgezeichnete Informatikdissertationen.

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

Thomas Gärtner, Hanna Geppert, Jürgen Bajorath, 2009, J. Chem. Inf. Model..

Active Search for Computer‐aided Drug Design

Roman Garnett, Thomas Gärtner, Dino Oglic, 2018, Molecular informatics.

On structured output training: hard cases and an efficient alternative

Thomas Gärtner, Shankar Vembu, Shankar Vembu, 2009, Machine Learning.

Optimization of Concurrent Engineering Projects using an Information-theoretic Complexity Metric

Thomas Gärtner, Christopher M. Schlick, Sönke Duckwitz, 2009 .

Direct Pattern Sampling with Respect to Pattern Frequency

Daniel Paurat, Thomas Gärtner, Claudio Lucchese, 2011, LWA.

Machine Learning and Knowledge Discovery in Databases

Thomas Gärtner, Francesco Bonchi, Neil Hurley, 2018, Lecture Notes in Computer Science.

A Complexity Measure for Concurrent Engineering Projects based on the DSM

Thomas Gärtner, Christopher M. Schlick, Sönke Duckwitz, 2008 .

Predicting unexpected influxes of players in EVE online

Roman Garnett, Thomas Gärtner, Timothy Ellersiek, 2014, 2014 IEEE Conference on Computational Intelligence and Games.

Why Kernels for Structured Data

Thomas Gärtner, T. Gärtner, 2008 .

Introducing the ‘active search’ method for iterative virtual screening

Roman Garnett, Thomas Gärtner, Jürgen Bajorath, 2015, Journal of Computer-Aided Molecular Design.

Radon Machines: Effective Parallelisation for Machine Learning

Thomas Gärtner, Mario Boley, Olana Missura, 2017, NIPS 2017.

Context-Based Clustering of Image Search Results

Thomas Gärtner, Stefan Wrobel, Hongqi Wang, 2009, KI.

Kernels and Distances for Structured Data

Thomas Gärtner, Peter A. Flach, John W. Lloyd, 2004, Machine Learning.

Kernel Methods in a Nutshell

Thomas Gärtner, T. Gärtner, 2008 .

A survey of kernels for structured data

Thomas Gärtner, T. Gärtner, Thomas Gärtner, 2003, SKDD.

On Graph Kernels: Hardness Results and Efficient Alternatives

Thomas Gärtner, Peter A. Flach, Stefan Wrobel, 2003, COLT.

Kernels for Structured Data

Thomas Gärtner, T. Gärtner, 2008, Series in Machine Perception and Artificial Intelligence.

Simpler knowledge-based support vector machines

Thomas Gärtner, Alexander J. Smola, Quoc V. Le, 2006, ICML.

Kernels for Predictive Graph Mining

Thomas Gärtner, Stefan Wrobel, Tamás Horváth, 2005, GfKl.

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

Thomas Gärtner, Gemma C. Garriga, Jens Humrich, 2011, 2011 IEEE 11th International Conference on Data Mining.

Graph Kernels

Thomas Gärtner, Stefan Wrobel, Tamás Horváth, 2017, Encyclopedia of Machine Learning and Data Mining.

Regularization path for Ranking SVM

Thomas Gärtner, Stéphane Canu, Gilles Gasso, 2008, ESANN.

Machine Learning and Knowledge Discovery in Databases

Thomas Gärtner, Francesco Bonchi, Neil Hurley, 2018, Lecture Notes in Computer Science.

Greedy Feature Construction

Thomas Gärtner, Dino Oglic, Dino Oglic, 2016, NIPS.

Counting-based Output Prediction for Orphan Screening

Thomas Gärtner, Katrin Ullrich, Christoph Stahr, 2010, LWA.

Active Search in Intensionally Specified Structured Spaces

Roman Garnett, Thomas Gärtner, Dino Oglic, 2017, AAAI.

Multi-Instance Kernels

Thomas Gärtner, Alexander J. Smola, Peter A. Flach, 2002, ICML.

On-Line Handwriting Recognition with Parallelized Machine Learning Algorithms

Thomas Gärtner, Stefan Wrobel, Sebastian Bothe, 2010, KI.

Graph kernels and Gaussian processes for relational reinforcement learning

Thomas Gärtner, Kurt Driessens, Jan Ramon, 2006, Machine Learning.

WBCsvm: Weighted Bayesian Classification based on Support Vector Machines

Thomas Gärtner, Peter A. Flach, 2001, ICML.

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

Thomas Gärtner, Michael Kamp, Mario Boley, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Model Selection for Ranking SVM Using Regularization Path

Thomas Gärtner, Stéphane Canu, Gilles Gasso, 2009 .

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

Céline Robardet, Thomas Gärtner, Andrea Passerini, 2016, Machine Learning.

Simulation Based Evaluation of Service Science Productivity for Solution Providers

Thomas Gärtner, Christopher M. Schlick, Sönke Duckwitz, 2010, Int. J. Serv. Sci. Manag. Eng. Technol..

Scalable Learning in Reproducing Kernel Krein Spaces

Thomas Gärtner, Dino Oglic, Dino Oglic, 2018, ICML.

Co-Regularised Support Vector Regression

Thomas Gärtner, Stefan Wrobel, Martin Vogt, 2017, ECML/PKDD.

Cyclic pattern kernels for predictive graph mining

Thomas Gärtner, Stefan Wrobel, Tamás Horváth, 2004, KDD.

The Cost of Learning Directed Cuts

Thomas Gärtner, Gemma C. Garriga, 2007, MLG.

A UWB solution for wireless intra‐spacecraft transmissions of sensor and SpaceWire data

Thomas Gärtner, Emanuel Puschita, Botond Sandor Kirei, 2019, Int. J. Satell. Commun. Netw..

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

Thomas Gärtner, Henrik Grosskreutz, Mario Boley, 2010, SDM.

On Structured Output Training: Hard Cases and an Efficient Alternative

Thomas Gärtner, Shankar Vembu, 2009, ECML/PKDD.

Semidefinite Ranking on Graphs

Thomas Gärtner, Stefan Wrobel, Shankar Vembu, 2007, MLG.

Model Selection for Ranking SVM Using

Thomas Gärtner, Stéphane Canu, Gilles Gasso, 2009 .

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

Thomas Gärtner, Michael Kamp, Mario Boley, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Scalability and Modularity as Dimensions of Flexibility of a Microsatellite Platform

Thomas Gärtner, Frank Dannemann, Michael Jetzschmann, 2017 .

Efficient co-regularised least squares regression

Thomas Gärtner, Ulf Brefeld, Stefan Wrobel, 2006, ICML.

A SIMULATION MODEL TO PREDICT IMPACTS OF ALTERATIONS IN DEVELOPMENT PROCESSES

Thomas Gärtner, Christopher M. Schlick, Norbert Rohleder, 2007 .

ScOSA - Scalable On-Board Computing for Space Avionics

Thomas Gärtner, Daniel Lüdtke, Kilian Johann Höflinger, 2018 .

Player Modeling for Intelligent Difficulty Adjustment

Thomas Gärtner, Olana Missura, Olana Missura, 2009, LWA.

Dynamic difficulty for checkers and Chinese chess

Thomas Gärtner, Jiaojian Wang, Olana Missura, 2012, 2012 IEEE Conference on Computational Intelligence and Games (CIG).

Towards Engaging Games

Thomas Gärtner, Kristian Kersting, Olana Missura, 2008, LWA.

DeSiM – A Simulation Tool for Project and Change Management on the Basis of Design Structure Matrices

Thomas Gärtner, Christopher M. Schlick, N. Rohleder, 2009 .

MLG 2006: Proceedings of the International Workshop on Mining and Learning with Graphs : in conjunction with ECML/PKDD 2006

Thorsten Meinl, Thomas Gärtner, Gemma C. Garriga, 2006 .

Transductive Gaussian Process Regression with Automatic Model Selection

Thomas Gärtner, Alexander J. Smola, Quoc V. Le, 2006, ECML.

Large Scale Learning with Kreĭn Kernels pdf

Thomas Gärtner, Dino Oglic, T. Gärtner, 2018, ArXiv.

Linear space direct pattern sampling using coupling from the past

Thomas Gärtner, Mario Boley, Sandy Moens, 2012, KDD.

Scalable Avionics for the DLR Micro- and Minisatellite Platforms S2TEP and COMPSAT

Thomas Gärtner, Frank Dannemann, Michael Jetzschmann, 2017 .

Kernels for structured data

Thomas Gärtner, Thomas Gärtner, 2008, Series in Machine Perception and Artificial Intelligence.

Graph Kernels

Thomas Gärtner, Stefan Wrobel, Tamás Horváth, 2010, Encyclopedia of Machine Learning.

Efficient Kernel Methods for Graphs

Thomas Gärtner, 2007, MLG.

Fisher Kernels for Logical Sequences

Thomas Gärtner, Kristian Kersting, K. Kersting, 2004, ECML.

Corresponding Projections for Orphan Screening pdf

Daniel Paurat, Thomas Gärtner, Sven Giesselbach, 2018, ArXiv.

Interactive Knowledge-Based Kernel PCA

Daniel Paurat, Thomas Gärtner, Dino Oglic, 2014, ECML/PKDD.

Kernel methods for graphs

Thomas Gärtner, 2005, MRDM '05.

A Linear Kernel on Strongly Typed Terms

Thomas Gärtner, Peter A. Flach, Thomas Gärtner, 2001 .

A Short Tour of Kernel Methods for Graphs

Thomas Gärtner, Quoc V. Le, Alex J Smola, 2005 .

Supervised PCA for Interactive Data Analysis

Daniel Paurat, Thomas Gärtner, Dino Oglic, 2013 .