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2020 – today
- 2024
[c39]Dennis J. N. J. Soemers, Guillaume Bams, Max Persoon, Marco Rietjens, Dimitar Sladic, Stefan Stefanov, Kurt Driessens
, Mark H. M. Winands:
Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games. CoG 2024: 1-4- [c38]Alexandros Doumanoglou, Dimitrios Zarpalas, Kurt Driessens:
Concept Basis Extraction for Latent Space Interpretation of Image Classifiers. VISIGRAPP (3): VISAPP 2024: 417-424 - [i4]Dennis J. N. J. Soemers, Guillaume Bams, Max Persoon, Marco Rietjens, Dimitar Sladic, Stefan Stefanov, Kurt Driessens, Mark H. M. Winands:
Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games. CoRR abs/2406.09242 (2024) - 2023
- [i3]Davide Nicotra, Miriam Lucio Martinez, Jacco Andreas de Vries, Marcel Merk, Kurt Driessens, Ronald Leonard Westra, Domenica Dibenedetto, Daniel Hugo Cámpora Pérez:
A quantum algorithm for track reconstruction in the LHCb vertex detector. CoRR abs/2308.00619 (2023) - 2021
- [i2]Tonio Weidler, Julian Lehnen, Quinton Denman, Dávid Sebok, Gerhard Weiss, Kurt Driessens, Mario Senden:
Biologically Inspired Semantic Lateral Connectivity for Convolutional Neural Networks. CoRR abs/2105.09830 (2021) - 2020
- [j9]Alexander Kroner, Mario Senden, Kurt Driessens, Rainer Goebel:
Contextual encoder-decoder network for visual saliency prediction. Neural Networks 129: 261-270 (2020) - [e2]Peggy Cellier, Kurt Driessens:
Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part I. Communications in Computer and Information Science 1167, Springer 2020, ISBN 978-3-030-43822-7 [contents] - [e1]Peggy Cellier, Kurt Driessens:
Machine Learning and Knowledge Discovery in Databases - International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Part II. Communications in Computer and Information Science 1168, Springer 2020, ISBN 978-3-030-43886-9 [contents]
2010 – 2019
- 2019
- [c37]René Raab, Kurt Driessens:
A Generative Policy Gradient Approach for Learning to Play Text-Based Adventure Games. BNAIC/BENELEARN 2019 - [i1]Alexander Kroner, Mario Senden, Kurt Driessens, Rainer Goebel:
Contextual Encoder-Decoder Network for Visual Saliency Prediction. CoRR abs/1902.06634 (2019) - 2018
- [c36]Dennis J. N. J. Soemers, Tim Brys, Kurt Driessens, Mark H. M. Winands, Ann Nowé:
Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. AAAI 2018: 7831-7836 - 2017
- [j8]Kurt Driessens, Dragi Kocev, Marko Robnik-Sikonja, Myra Spiliopoulou:
Introduction to the special issue dedicated to the Journal Track of ECML PKDD 2017. Data Min. Knowl. Discov. 31(5): 1155-1156 (2017) - [j7]Kurt Driessens, Dragi Kocev, Marko Robnik-Sikonja, Myra Spiliopoulou:
Introduction to the special issue dedicated to the Journal Track of ECML PKDD 2017. Mach. Learn. 106(9-10): 1243-1244 (2017) - [j6]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers, Kurt Driessens, Ralf Peeters:
Testing exchangeability for transfer decision. Pattern Recognit. Lett. 88: 64-71 (2017) - [c35]David Roschewitz, Kurt Driessens, Pieter Collins:
Simultaneous Ensemble Generation and Hyperparameter Optimization for Regression. BNCAI 2017: 116-130 - [c34]Pietro Bonizzi, Kurt Driessens, Joël M. H. Karel:
Detection of Atrial Fibrillation Episodes from Short Single Lead Recordings by Means of Ensemble Learning. CinC 2017 - [c33]Kurt Driessens, Irena Koprinska, Olga C. Santos, Evgueni N. Smirnov, Kalina Yacef, Osmar R. Zaïane:
UMAP 2017 EdRecSys Workshop Organizers' Welcome & Organization. UMAP (Adjunct Publication) 2017: 125-127 - [c32]Mara Houbraken, Chang Sun, Evgueni N. Smirnov, Kurt Driessens:
Discovering Hidden Course Requirements and Student Competences from Grade Data. UMAP (Adjunct Publication) 2017: 147-152 - [r2]Kurt Driessens:
Relational Reinforcement Learning. Encyclopedia of Machine Learning and Data Mining 2017: 1096-1103 - 2016
- [c31]Damien Lejeune, Kurt Driessens:
A Data Driven Similarity Measure and Example Mapping Function for General, Unlabelled Data Sets. ECAI 2016: 158-166 - [c30]Sjoerd van Steenkiste, Jan Koutník, Kurt Driessens, Jürgen Schmidhuber:
A Wavelet-based Encoding for Neuroevolution. GECCO 2016: 517-524 - 2015
- [j5]Decebal Constantin Mocanu, Haitham Bou-Ammar, Dietwig Lowet, Kurt Driessens, Antonio Liotta, Gerhard Weiss, Karl Tuyls:
Factored four way conditional restricted Boltzmann machines for activity recognition. Pattern Recognit. Lett. 66: 100-108 (2015) - [c29]Shuang Zhou, Gijs Schoenmakers, Evgueni N. Smirnov, Ralf Peeters, Kurt Driessens, Siqi Chen:
Largest Source Subset Selection for Instance Transfer. ACML 2015: 423-438 - [c28]Shuang Zhou, Evgueni N. Smirnov, Gijs Schoenmakers, Ralf Peeters, Kurt Driessens:
A Non-parametric Conformity-Based Test for Transfer Decisions. ICTAI 2015: 628-635 - 2013
- [c27]Samuel Sarjant, Bernhard Pfahringer, Kurt Driessens, Tony Smith:
A Direct Policy-Search Algorithm for Relational Reinforcement Learning. ILP 2013: 76-92 - [c26]Haitham Bou-Ammar, Decebal Constantin Mocanu, Matthew E. Taylor, Kurt Driessens, Karl Tuyls, Gerhard Weiss:
Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines. ECML/PKDD (2) 2013: 449-464 - 2012
- [c25]Haitham Bou-Ammar, Karl Tuyls, Matthew E. Taylor, Kurt Driessens, Gerhard Weiss:
Reinforcement learning transfer via sparse coding. AAMAS 2012: 383-390 - 2011
- [c24]Samuel Sarjant, Bernhard Pfahringer, Kurt Driessens, Tony Smith:
Using the online cross-entropy method to learn relational policies for playing different games. CIG 2011: 182-189 - [c23]Elena Ikonomovska, Kurt Driessens, Saso Dzeroski, João Gama:
Adaptive Windowing for Online Learning from Multiple Inter-related Data Streams. ICDM Workshops 2011: 697-704 - 2010
- [p1]Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens, H. Jaap van den Herik, Eric O. Postma:
Learning with Whom to Communicate Using Relational Reinforcement Learning. Interactive Collaborative Information Systems 2010: 45-63 - [r1]Kurt Driessens:
Relational Reinforcement Learning. Encyclopedia of Machine Learning 2010: 857-862
2000 – 2009
- 2009
- [c22]Guy Van den Broeck, Kurt Driessens, Jan Ramon:
Monte-Carlo Tree Search in Poker Using Expected Reward Distributions. ACML 2009: 367-381 - [c21]Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens:
Learning with whom to communicate using relational reinforcement learning. AAMAS (2) 2009: 1221-1222 - [c20]Scott Sanner, Robby Goetschalckx, Kurt Driessens, Guy Shani:
Bayesian Real-Time Dynamic Programming. IJCAI 2009: 1784-1789 - 2008
- [c19]Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, Kurt Driessens, Karl Tuyls:
Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. AAAI 2008: 1485-1486 - [c18]Robby Goetschalckx, Scott Sanner, Kurt Driessens:
Reinforcement Learning with the Use of Costly Features. ECAI 2008: 779-780 - [c17]Laura-Andreea Antanas, Kurt Driessens, Jan Ramon, Tom Croonenborghs:
Using Decision Trees as the Answer Networks in Temporal Difference-Networks. ECAI 2008: 847-848 - [c16]Robby Goetschalckx, Scott Sanner, Kurt Driessens:
Reinforcement Learning with the Use of Costly Features. EWRL 2008: 124-135 - [c15]Robby Goetschalckx, Kurt Driessens, Scott Sanner:
Cost-Sensitive Parsimonious Linear Regression. ICDM 2008: 809-814 - [c14]Kristian Kersting, Kurt Driessens:
Non-parametric policy gradients: a unified treatment of propositional and relational domains. ICML 2008: 456-463 - 2007
- [c13]Jan Ramon, Kurt Driessens, Tom Croonenborghs:
Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling. ECML 2007: 699-707 - [c12]Tom Croonenborghs, Kurt Driessens, Maurice Bruynooghe:
Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning. ILP 2007: 88-97 - 2006
- [j4]Kurt Driessens, Jan Ramon, Thomas Gärtner:
Graph kernels and Gaussian processes for relational reinforcement learning. Mach. Learn. 64(1-3): 91-119 (2006) - [c11]Kurt Driessens, Peter Reutemann, Bernhard Pfahringer, Claire Leschi:
Using Weighted Nearest Neighbor to Benefit from Unlabeled Data. PAKDD 2006: 60-69 - 2005
- [j3]Kurt Driessens:
Relational reinforcement learning. AI Commun. 18(1): 71-73 (2005) - [c10]Kurt Driessens, Saso Dzeroski:
Combining Model-Based and Instance-Based Learning for First Order Regression. BNAIC 2005: 341-342 - [c9]Kurt Driessens, Saso Dzeroski:
Combining model-based and instance-based learning for first order regression. ICML 2005: 193-200 - 2004
- [j2]Kurt Driessens, Saso Dzeroski:
Integrating Guidance into Relational Reinforcement Learning. Mach. Learn. 57(3): 271-304 (2004) - 2003
- [c8]Kurt Driessens, Jan Ramon:
Relational Instance Based Regression for Relational Reinforcement Learning. ICML 2003: 123-130 - [c7]Thomas Gärtner, Kurt Driessens, Jan Ramon:
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. ILP 2003: 146-163 - 2002
- [c6]Kurt Driessens, Saso Dzeroski:
Integrating Experimentation and Guidance in Relational Reinforcement Learning. ICML 2002: 115-122 - 2001
- [j1]Saso Dzeroski, Luc De Raedt, Kurt Driessens:
Relational Reinforcement Learning. Mach. Learn. 43(1/2): 7-52 (2001) - [c5]Kurt Driessens:
Relational Reinforcement Learning. EASSS 2001: 271-280 - [c4]Kurt Driessens, Jan Ramon, Hendrik Blockeel:
Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. ECML 2001: 97-108
1990 – 1999
- 1998
- [c3]Nico Jacobs, Kurt Driessens, Luc De Raedt:
Inductive verification and validation of multi agent systems. EUROVAV 1998 - [c2]Nico Jacobs, Kurt Driessens, Luc De Raedt:
Using ILP-Systems for Verification and Validation of Multi-agent Systems. ILP 1998: 145-154 - [c1]Kurt Driessens, Nico Jacobs, Nathalie Cossement, Patrick Monsieurs, Luc De Raedt:
Inductive Verification and Validation of the KULRoT RoboCup Team. RoboCup 1998: 193-206
Coauthor Index
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