Herke van Hoof
TitleCited byYear
Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks
O Kroemer, C Daniel, G Neumann, H van Hoof, J Peters
Proceedings of the International Conference on Robotics and Automation, 2015
502015
Addressing Function Approximation Error in Actor-Critic Methods
S Fujimoto, H van Hoof, D Meger
arXiv preprint arXiv:1802.09477, 2018
472018
Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments
H van Hoof, O Kroemer, J Peters
IEEE Transactions on Robotics, 2014
472014
Learning Robot In-Hand Manipulation with Tactile Features
H van Hoof, T Hermans, G Neumann, J Peters
412015
Probabilistic inference for determining options in reinforcement learning
C Daniel, H Van Hoof, J Peters, G Neumann
Machine Learning 104 (2-3), 337-357, 2016
382016
Maximally Informative Interaction Learning for Scene Exploration
H van Hoof, O Kroemer, HB Amor, J Peters
Intelligent Robots and Systems, 2012
342012
Stabilizing novel objects by learning to predict tactile slip
F Veiga, H Van Hoof, J Peters, T Hermans
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
322015
Learning to Predict Phases of Manipulation Tasks as Hidden States
O Kroemer, H van Hoof, G Neumann, J Peters
IEEE International Conference on Robotics and Automation, 2014
322014
Learning of Non-Parametric Control Policies with High-Dimensional State Features
H van Hoof, J Peters, G Neumann
Proceedings of the Eighteenth International Conference on Artificial …, 2015
312015
Stable reinforcement learning with autoencoders for tactile and visual data
H van Hoof, N Chen, M Karl, P van der Smagt, J Peters
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
282016
Active tactile object exploration with gaussian processes
Z Yi, R Calandra, F Veiga, H van Hoof, T Hermans, Y Zhang, J Peters
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
212016
Policy Search For Learning Robot Control Using Sparse Data
B Bischoff, D Nguyen-Tuong, H van Hoof, A McHutchon, CE Rasmussen, ...
International Conference on Robotics and Automation, 2014
152014
Non-parametric policy search with limited information loss
H Van Hoof, G Neumann, J Peters
The Journal of Machine Learning Research 18 (1), 2472-2517, 2017
102017
Probabilistic Interactive Segmentation for Anthropomorphic Robots in Cluttered Environments
H van Hoof, O Kroemer, J Peters
International Conference on Humanoid Robotics, 2013
102013
BanditSum: Extractive Summarization as a Contextual Bandit
Y Dong, Y Shen, E Crawford, H van Hoof, JCK Cheung
arXiv preprint arXiv:1809.09672, 2018
32018
An Inference-Based Policy Gradient Method for Learning Options
M Smith, H Hoof, J Pineau
International Conference on Machine Learning, 4710-4719, 2018
32018
Generalized exploration in policy search
H van Hoof, D Tanneberg, J Peters
Machine Learning 106 (9-10), 1705-1724, 2017
32017
Policy search with high-dimensional context variables
V Tangkaratt, H van Hoof, S Parisi, G Neumann, J Peters, M Sugiyama
Thirty-First AAAI Conference on Artificial Intelligence, 2017
22017
Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
W Kool, H van Hoof, M Welling
arXiv preprint arXiv:1903.06059, 2019
2019
Uncertainty Aware Learning from Demonstrations in Multiple Contexts using Bayesian Neural Networks
S Thakur, H van Hoof, JCG Higuera, D Precup, D Meger
arXiv preprint arXiv:1903.05697, 2019
2019
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Articles 1–20