Herke van Hoof

According to our database, Herke van Hoof authored at least 66 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Planning with a Learned Policy Basis to Optimally Solve Complex Tasks.

Guillermo Infante, David Kuric, Anders Jonsson, Vicenç Gómez, Herke van Hoof

CoRR, 2024

2023

Reusable Options through Gradient-based Meta Learning.

David Kuric, Herke van Hoof

Trans. Mach. Learn. Res., 2023

Hierarchical Reinforcement Learning for Power Network Topology Control.

Blazej Manczak, Jan Viebahn, Herke van Hoof

CoRR, 2023

Uncoupled Learning of Differential Stackelberg Equilibria with Commitments.

Robert Tyler Loftin, Mustafa Mert Çelikok, Herke van Hoof, Samuel Kaski, Frans A. Oliehoek

CoRR, 2023

Learning Hierarchical Planning-Based Policies from Offline Data.

Jan Wöhlke, Felix Schmitt, Herke van Hoof

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Learning Objective-Specific Active Learning Strategies with Attentive Neural Processes.

Tim Bakker, Herke van Hoof, Max Welling

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Bridge the Inference Gaps of Neural Processes via Expectation Maximization.

Qi Wang, Marco Federici, Herke van Hoof

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Exposure-Aware Recommendation using Contextual Bandits.

Masoud Mansoury, Bamshad Mobasher, Herke van Hoof

CoRR, 2022

Calculus on MDPs: Potential Shaping as a Gradient.

Erik Jenner, Herke van Hoof, Adam Gleave

CoRR, 2022

Reliably Re-Acting to Partner's Actions with the Social Intrinsic Motivation of Transfer Empowerment.

Tessa van der Heiden, Herke van Hoof, Efstratios Gavves, Christoph Salge

CoRR, 2022

Learning Expressive Meta-Representations with Mixture of Expert Neural Processes.

Qi Wang, Herke van Hoof

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Neural Topological Ordering for Computation Graphs.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Charul Giri, Ole-Christoffer Granmo, Herke van Hoof, Christian D. Blakely

Proceedings of the International Joint Conference on Neural Networks, 2022

Value Refinement Network (VRN).

Jan Wöhlke, Felix Schmitt, Herke van Hoof

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Leveraging Class Abstraction for Commonsense Reinforcement Learning via Residual Policy Gradient Methods.

Niklas Höpner, Ilaria Tiddi, Herke van Hoof

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

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

Qi Wang, Herke van Hoof

Proceedings of the International Conference on Machine Learning, 2022

Multi-Agent MDP Homomorphic Networks.

Elise van der Pol, Herke van Hoof, Frans A. Oliehoek, Max Welling

Proceedings of the Tenth International Conference on Learning Representations, 2022

Deep Policy Dynamic Programming for Vehicle Routing Problems.

Wouter Kool, Herke van Hoof, Joaquim A. S. Gromicho, Max Welling

Proceedings of the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2022

Fast and Data Efficient Reinforcement Learning from Pixels via Non-parametric Value Approximation.

Alexander Long, Alan Blair, Herke van Hoof

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

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

Shihan Wang, Chao Zhang, Ben J. A. Kröse, Herke van Hoof

J. Medical Syst., 2021

A Survey of Exploration Methods in Reinforcement Learning.

Susan Amin, Maziar Gomrokchi, Harsh Satija, Herke van Hoof, Doina Precup

CoRR, 2021

Combining Reward Information from Multiple Sources.

Dmitrii Krasheninnikov, Rohin Shah, Herke van Hoof

CoRR, 2021

Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models.

Qi Wang, Herke van Hoof

CoRR, 2021

Hierarchies of Planning and Reinforcement Learning for Robot Navigation.

Jan Wöhlke, Felix Schmitt, Herke van Hoof

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Deep Coherent Exploration for Continuous Control.

Yijie Zhang, Herke van Hoof

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement.

Wouter Kool, Herke van Hoof, Max Welling

J. Mach. Learn. Res., 2020

Robust Multi-Agent Reinforcement Learning with Social Empowerment for Coordination and Communication.

Tessa van der Heiden, Christoph Salge, Efstratios Gavves, Herke van Hoof

CoRR, 2020

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

Joris Mollinga, Herke van Hoof

CoRR, 2020

Social navigation with human empowerment driven reinforcement learning.

Tessa van der Heiden, Christian Weiss, Naveen Shankar Nagaraja, Herke van Hoof

CoRR, 2020

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

Zeynep Akata, Dan Balliet, Maarten de Rijke, Frank Dignum, Virginia Dignum, Guszti Eiben, Antske Fokkens, Davide Grossi, Koen V. Hindriks, Holger H. Hoos, Hayley Hung, Catholijn M. Jonker, Christof Monz, Mark A. Neerincx, Frans A. Oliehoek, Henry Prakken, Stefan Schlobach, Linda C. van der Gaag, Frank van Harmelen, Herke van Hoof, Birna van Riemsdijk, Aimee van Wynsberghe, Rineke Verbrugge, Bart Verheij, Piek Vossen, Max Welling

Computer, 2020

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

Jin Huang, Harrie Oosterhuis, Maarten de Rijke, Herke van Hoof

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning.

Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Experimental design for MRI by greedy policy search.

Tim Bakker, Herke van Hoof, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Doubly Stochastic Variational Inference for Neural Processes with Hierarchical Latent Variables.

Qi Wang, Herke van Hoof

Proceedings of the 37th International Conference on Machine Learning, 2020

Estimating Gradients for Discrete Random Variables by Sampling without Replacement.

Wouter Kool, Herke van Hoof, Max Welling

Proceedings of the 8th International Conference on Learning Representations, 2020

Social Navigation with Human Empowerment Driven Deep Reinforcement Learning.

Tessa van der Heiden, Florian Mirus, Herke van Hoof

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

A Performance-Based Start State Curriculum Framework for Reinforcement Learning.

Jan Wöhlke, Felix Schmitt, Herke van Hoof

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales.

Sanjay Thakur, Herke van Hoof, Gunshi Gupta, David Meger

CoRR, 2019

Stochastic Activation Actor Critic Methods.

Wenling Shang, Douwe van der Wal, Herke van Hoof, Max Welling

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Deep Generative Modeling of LiDAR Data.

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

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks.

Sanjay Thakur, Herke van Hoof, Juan Camilo Gamboa Higuera, Doina Precup, David Meger

Proceedings of the International Conference on Robotics and Automation, 2019

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

Wouter Kool, Herke van Hoof, Max Welling

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

Buy 4 REINFORCE Samples, Get a Baseline for Free!

Wouter Kool, Herke van Hoof, Max Welling

Proceedings of the Deep Reinforcement Learning Meets Structured Prediction, 2019

Attention, Learn to Solve Routing Problems!

Wouter Kool, Herke van Hoof, Max Welling

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

2018

Reinforcement Learning with Non-uniform State Representations for Adaptive Search.

Sandeep Manjanna, Herke van Hoof, Gregory Dudek

Proceedings of the 2018 IEEE International Symposium on Safety, 2018

Policy Search on Aggregated State Space for Active Sampling.

Sandeep Manjanna, Herke van Hoof, Gregory Dudek

Proceedings of the 2018 International Symposium on Experimental Robotics, 2018

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

Victor Barbaros, Herke van Hoof, Abbas Abdolmaleki, David Meger

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

An Inference-Based Policy Gradient Method for Learning Options.

Matthew J. A. Smith, Herke van Hoof, Joelle Pineau

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

Addressing Function Approximation Error in Actor-Critic Methods.

Scott Fujimoto, Herke van Hoof, David Meger

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

BanditSum: Extractive Summarization as a Contextual Bandit.

Yue Dong, Yikang Shen, Eric Crawford, Herke van Hoof, Jackie Chi Kit Cheung

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

2017

Generalized exploration in policy search.

Herke van Hoof, Daniel Tanneberg, Jan Peters

Mach. Learn., 2017

Non-parametric Policy Search with Limited Information Loss.

Herke van Hoof, Gerhard Neumann, Jan Peters

J. Mach. Learn. Res., 2017

Policy Search with High-Dimensional Context Variables.

Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, Masashi Sugiyama

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

2016

Machine learning through exploration for perception-driven robotics = Machinelles Lernen in der Perzeptions-basierte Robotik.

Herke van Hoof

PhD thesis, 2016

Probabilistic inference for determining options in reinforcement learning.

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

Mach. Learn., 2016

Active tactile object exploration with Gaussian processes.

Zhengkun Yi, Roberto Calandra, Filipe Veiga, Herke van Hoof, Tucker Hermans, Yilei Zhang, Jan Peters

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Stable reinforcement learning with autoencoders for tactile and visual data.

Herke van Hoof, Nutan Chen, Maximilian Karl, Patrick van der Smagt, Jan Peters

Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

2015

Stabilizing novel objects by learning to predict tactile slip.

Filipe Veiga, Herke van Hoof, Jan Peters, Tucker Hermans

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Towards learning hierarchical skills for multi-phase manipulation tasks.

Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke van Hoof, Jan Peters

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Learning robot in-hand manipulation with tactile features.

Herke van Hoof, Tucker Hermans, Gerhard Neumann, Jan Peters

Proceedings of the 15th IEEE-RAS International Conference on Humanoid Robots, 2015

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

Herke van Hoof, Jan Peters, Gerhard Neumann

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments.

Herke van Hoof, Oliver Kroemer, Jan Peters

IEEE Trans. Robotics, 2014

Learning to predict phases of manipulation tasks as hidden states.

Oliver Kroemer, Herke van Hoof, Gerhard Neumann, Jan Peters

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Policy search for learning robot control using sparse data.

Bastian Bischoff, Duy Nguyen-Tuong, Herke van Hoof, Andrew McHutchon, Carl E. Rasmussen, Alois C. Knoll, Jan Peters, Marc Peter Deisenroth

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

2013

Probabilistic interactive segmentation for anthropomorphic robots in cluttered environments.

Herke van Hoof, Oliver Kroemer, Jan Peters

Proceedings of the 13th IEEE-RAS International Conference on Humanoid Robots, 2013

2012

Maximally informative interaction learning for scene exploration.

Herke van Hoof, Oliver Kroemer, Heni Ben Amor, Jan Peters

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012