Publications

Conference and journal papers

2024

Mansoury, Masoud; Mobasher, Bamshad; van Hoof, Herke

Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits Proceedings Article Forthcoming

In: ACM International Conference on Information and Knowledge Management, Forthcoming.

BibTeX

Giri, Charul; Granmo, Ole Christoffer; van Hoof, Herke

Accelerated Tsetlin Machine Inference Through Incremental Model Re-evaluation Proceedings Article Forthcoming

In: International Symposium on Tsetlin Machines, Forthcoming.

BibTeX

Huang, Jin; Oosterhuis, Harrie; Mansoury, Masoud; van Hoof, Herke; de Rijke, Maarten

Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems Proceedings Article Forthcoming

In: International ACM SIGIR Conference on Research and Development in Information Retrieval, Forthcoming.

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Kuric, D.; Infante, G.; Gómez, V.; Jonsson, A.; van Hoof, H.

Planning with a Learned Policy Basis to Optimally Solve Complex Tasks Proceedings Article

In: International Conference on Automated Planning and Scheduling, 2024.

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Loftin, Robert; Çelikok, Mustafa Mert; van Hoof, Herke; Kaski, Samuel; Oliehoek, Frans

Uncoupled Learning of Differential Stackelberg Equilibria with Commitments Proceedings Article

In: Artificial Agents and Multi-Agent Systems (AAMAS), 2024.

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2023

Woehlke, J.; Schmitt, F.; van Hoof, H.

Learning Hierarchical Planning-Based Policies from Offline Data Proceedings Article

In: Machine Learning and Knowledge Discovery in Databases: Research Track (ECML PKDD), 2023.

BibTeX

Bakker, T.; van Hoof, H.; Welling, M.

Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes Proceedings Article

In: Machine Learning and Knowledge Discovery in Databases: Research Track (ECML PKDD), 2023.

BibTeX

Wang, Qi; Federici, Marco; Hoof, Herke

Bridge the Inference Gaps of Neural Processes via Expectation Maximization Proceedings Article

In: International Conference on Learning Representations, 2023.

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Kuric, David; Hoof, Herke

Reusable Options through Gradient-based Meta Learning Journal Article

In: Transactions on Machine Learning Research, vol. 03/2023, 2023.

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2022

Wang, Qi; Hoof, Herke

Learning Expressive Meta-Representations with Mixture of Expert Neural Processes Proceedings Article

In: Advances in Neural Information Processing Systems, 2022.

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Gagrani, Mukul; Rainone, Corrado; Yang, Yang; Teague, Harris; Jeon, Wonseok; Hoof, Herke; Zeng, Weiliang Will; Zappi, Piero; Lott, Christopher; Bondesan, Roberto

Neural Topological Ordering for Computation Graphs Proceedings Article

In: Advances in Neural Information Processing Systems, 2022.

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Wöhlke, Jan; Schmitt, Felix; Hoof, Herke

Value Refinement Network (VRN) Proceedings Article

In: International Joint Conference on Artificial Intelligence, 2022.

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Höpner, Niklas; Tiddi, Ilaria; Hoof, Herke

Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods Proceedings Article

In: International Joint Conference on Artificial Intelligence, 2022.

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Giri, Charul; Granmo, Ole-Christopher; Hoof, Herke; Blakely, Christian D.

Logic-based AI for Interpretable Board Game Winner Prediction with Tsetlin Machine Proceedings Article

In: International Joint Conference on Neural Networks, 2022.

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Wang, Qi; Hoof, Herke

Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search Proceedings Article

In: International Conference on Machine Learning, 2022.

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Kool, Wouter; Hoof, Herke; Gromicho, Joaquim; Welling, Max

Deep Policy Dynamic Programming for Vehicle Routing Problems Proceedings Article

In: International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2022.

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Pol, Elise; Hoof, Herke; Oliehoek, Frans; Welling, Max

Multi-Agent MDP Homomorphic Networks Proceedings Article

In: Proceedings of the International Conference on Learning Representations, 2022.

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Long, Alex; Blair, Alan; Hoof, Herke

Fast and Data Efficient Reinforcement Learning from Pixels via Non-Parametric Value Approximation Proceedings Article

In: AAAI National Conference on Artificial Intelligence, 2022.

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2021

Wang, Shihan; Zhang, Chao; Kröse, Ben; Hoof, Herke

Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator Journal Article

In: Journal of Medical Systems, vol. 45, no. 102, 2021.

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Zhang, Yijie; Hoof, Herke

Deep Coherent Exploration For Continuous Control Proceedings Article

In: International Conference on Machine Learning, 2021.

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Wöhlke, J.; Schmitt, F.; Hoof, H.

Hierarchies of Planning and Reinforcement Learning for Robot Navigation Proceedings Article

In: IEEE International Conference on Robotics and Automation, 2021.

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Wang, S.; Sporrel, K.; Hoof, H.; Simons, M.; Boer, R.; Ettema, D.; Nibbeling, N.; Deutekom, M.; Kröse, B.

Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application: A Feasibility Study Journal Article

In: International Journal of Environmental Research and Public Health, Special Issue, 2021.

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2020

Pol, Elise; Worrall, Daniel; Hoof, Herke; Oliehoek, Frans; Welling, Max

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning Proceedings Article

In: Advances in Neural Information Processing Systems, 2020.

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Bakker, Tim; Hoof, Herke; Welling, Max

Experimental design for MRI by greedy policy search Proceedings Article

In: Advances in Neural Information Processing Systems, 2020.

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Huang, Jin; Oosterhuis, Harrie; Rijke, Maarten; Hoof, Herke

Keeping Dataset Biases out of the Simulation: A Debiased Simulator for Reinforcement Learning based Recommender Systems Proceedings Article

In: The ACM Conference on Recommender Systems, 2020.

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Heide, Tessa; Mirus, Florian; Hoof, Herke

Social Navigation with Human Empowerment Driven Reinforcement Learning Proceedings Article

In: International Conference on Artificial Neural Networks, 2020.

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Akata, Zeynep; Balliet, Dan; Rijke, Maarten; Dignum, Frank; Dignum, Virginia; Eiben, Guszti; others,

A Research Agenda for Hybrid Intelligence: Augmenting Human Intellect With Collaborative, Adaptive, Responsible, and Explainable Artificial Intelligence Journal Article

In: Computer, vol. 53, no. 8, pp. 18–28, 2020.

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Wang, Qi; Hoof, Herke

Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables Proceedings Article

In: International Conference on Machine Learning, 2020.

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Mollinga, Jasper; Hoof, Herke

An Autonomous Free Airspace En-route Controller using Deep Reinforcement Learning Techniques Proceedings Article

In: International Conference on Research in Air Transportation, 2020.

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Wöhlke, Jan; Schmitt, Felix; Hoof, Herke

A Performance-Based Start State Curriculum Framework for Reinforcement Learning Proceedings Article

In: International Conference on Autonomous Agents and Multi-Agent Systems, 2020.

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Kool, Wouter; Hoof, Herke; Welling, Max

Estimating Gradients for Discrete Random Variables by Sampling without Replacement Proceedings Article

In: International Conference on Learning Representations, 2020.

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Kool, W.; Hoof, H.; Welling, M.

Ancestral Gumbel-Top-k Sampling for Sampling without Replacement Journal Article

In: Journal of Machine Learning Research, vol. 21, no. 47, pp. 1–36, 2020.

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2019

Caccia, Lucas; Hoof, Herke; Courville, Aaron C.; Pineau, Joelle

Deep Generative Modeling of LiDAR Data Proceedings Article

In: IEEE International Conference on Intelligent Robots and Systems, 2019.

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Shang, Wenling; Wal, Douwe; Hoof, Herke; Welling, Max

Stochastic Activation Actor Critic Methods Proceedings Article

In: European Conference on Machine Learning, 2019.

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Kool, Wouter; Hoof, Herke Van; Welling, Max

Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement Proceedings Article

In: International Conference on Machine Learning, pp. 3499–3508, 2019.

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Thakur, S.; Hoof, H.; Higuera, J. C. Gamboa; Precup, D.; Meger, D.

Uncertainty aware Imitation Learning on Multiple Tasks using Bayesian Neural Networks Proceedings Article

In: International Conference on Robotics and Automation, 2019.

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Kool, Wouter; Hoof, Herke; Welling, Max

Attention! Learn to solve routing problems! Proceedings Article

In: International Conference on Learning Representations, 2019.

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2018

Manjanna, S.; Hoof, H.; Dudek, G.

Policy Search on Aggregated State Space for Active Sampling Proceedings Article

In: International Symposium on Experimental Robotics, 2018.

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Dong, Y.; Shen, Y.; Crawford, E.; Hoof, H.; Cheung, J. C. K.

BanditSum: Extractive Summarization as a Contextual Bandit Proceedings Article

In: Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 3739–3748, 2018.

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Manjanna, S.; Hoof, H.; Dudek, G.

Reinforcement Learning with Non-uniform State Representations for Adaptive Search Proceedings Article

In: IEEE International Symposium on Safety, Security, and Rescue Robotics, 2018.

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Fujimoto, S.; Hoof, H.; Meger, D.

Addressing function approximation error in actor-critic methods Proceedings Article

In: International Conference on Machine Learning, pp. 1587–1596, 2018.

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Smith, M.; Hoof, H.; Pineau, J.

An Inference-Based Policy Gradient Method for Learning Options Proceedings Article

In: International Conference on Machine Learning, pp. 4703-4712, 2018.

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Barbaros, V.; Hoof, H.; Abdolmaleki, A.; Meger, D.

Eager and Memory-Based Non-Parametric Stochastic Search Methods for Learning Control Proceedings Article

In: International Conference on Robotics and Automation, 2018.

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2017

Hoof, H. Van; Neumann, G.; Peters, J.

Non-parametric Policy Search with Limited Information Loss Journal Article

In: Journal of Machine Learning Research, vol. 18, no. 73, pp. 1-46, 2017.

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Hoof, Herke; Tanneberg, Daniel; Peters, Jan

Generalized Exploration in Policy Search Journal Article

In: Machine Learning - Special issue ECML PKDD, vol. 106, no. 9–10, pp. 1705–1724, 2017, ISSN: 1573-0565.

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Tangkaratt, V.; Hoof, H.; Parisi, S.; Neumann, G.; Peters, J.; Sugiyama, M.

Policy Search with High-Dimensional Context Variables Proceedings Article

In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp. 2632–2638, 2017.

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2016

Daniel, Christian; Hoof, Herke; Neumann, Gerhard; Peters, Jan

Probabilistic Inference for Determining Options in Reinforcement Learning Journal Article

In: Machine Learning - Special issue ECML PKDD, vol. 104, no. 2–3, pp. 337–357, 2016.

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Hoof, Herke; Chen, Nutan; Karl, Maximilian; Smart, Patrick; Peters, Jan

Stable Reinforcement Learning with Auto-Encoders for Tactile and Visual Data Proceedings Article

In: International Conference on Intelligent Robots and Systems, pp. 3928–3934, 2016.

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Yi, Z.; Calandra, R.; Veiga, F.; Hoof, H.; Hermans, T.; Zhang, Y.; Peters, J.

Active Tactile Object Exploration with Gaussian Processes Proceedings Article

In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 4925–4930, 2016.

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2015

Hoof, Herke; Peters, Jan; Neumann, Gerhard

Learning of Non-Parametric Control Policies with High-Dimensional State Features Proceedings Article

In: International Conference on Artificial Intelligence and Statistics, pp. 1004–1012, 2015.

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Hoof, H.; Hermans, T.; Neumann, G.; Peters, J.

Learning Robot In-Hand Manipulation with Tactile Features Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2015.

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Veiga, F. F.; Hoof, H.; Peters, J.; Hermans, T.

Stabilizing Novel Objects by Learning to Predict Tactile Slip Proceedings Article

In: Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS), pp. 5065–5072, 2015.

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Kroemer, O.; Daniel, C.; Neumann, G; Hoof, H.; Peters, J.

Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks Proceedings Article

In: Proceedings of the International Conference on Robotics and Automation (ICRA), 2015.

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2014

Hoof, Herke; Kroemer, Oliver; Peters, Jan

Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments Journal Article

In: IEEE Transactions on Robotics (TRo), vol. 5, pp. 1198-1209, 2014.

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Kroemer, O.; Hoof, H.; Neumann, G.; Peters, J.

Learning to Predict Phases of Manipulation Tasks as Hidden States Proceedings Article

In: Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA), 2014.

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Bischoff, B.; Nguyen-Tuong, D.; Hoof, H.; McHutchon, A.; Rasmussen, C. E.; Knoll, A.; Peters, J.; Deisenroth, M. P.

Policy Search For Learning Robot Control Using Sparse Data Proceedings Article

In: Proceedings of 2014 IEEE International Conference on Robotics and Automation (ICRA), 2014.

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2013

Hoof, H.; Kroemer, O; Peters, J.

Probabilistic Interactive Segmentation for Anthropomorphic Robots in Cluttered Environments Proceedings Article

In: Proceedings of the International Conference on Humanoid Robots (HUMANOIDS), 2013.

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2012

Hoof, H.; Kroemer, O.; Amor, H. Ben; Peters, J.

Maximally Informative Interaction Learning for Scene Exploration Proceedings Article

In: Proceedings of the International Conference on Robot Systems (IROS), 2012.

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2011

Hoof, H.; Zant, T.; Wiering, M. A.

Adaptive Visual Face Tracking for an Autonomous Robot Proceedings Article

In: Proceedings of the Belgian-Dutch Artificial Intelligence Conference (BNAIC 11), 2011.

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Ph.D. Thesis

2016

Hoof, H.

Machine Learning through Exploration for Perception-Driven Robotics PhD Thesis

2016.

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