Herke van Hoof
Herke van Hoof
Vahvistettu sähköpostiosoite verkkotunnuksessa uva.nl - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Addressing function approximation error in actor-critic methods
S Fujimoto, H Hoof, D Meger
International Conference on Machine Learning, 1587-1596, 2018
10592018
Attention, Learn to Solve Routing Problems!
W Kool, H van Hoof, M Welling
arXiv preprint arXiv:1803.08475, 2018
2692018
Learning Robot In-Hand Manipulation with Tactile Features
H van Hoof, T Hermans, G Neumann, J Peters
1082015
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
982016
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
952015
Probabilistic inference for determining options in reinforcement learning
C Daniel, H Van Hoof, J Peters, G Neumann
Machine Learning 104 (2), 337-357, 2016
892016
BanditSum: Extractive Summarization as a Contextual Bandit
Y Dong, Y Shen, E Crawford, H van Hoof, JCK Cheung
arXiv preprint arXiv:1809.09672, 2018
832018
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
692015
Probabilistic Segmentation and Targeted Exploration of Objects in Cluttered Environments
H van Hoof, O Kroemer, J Peters
IEEE Transactions on Robotics, 2014
692014
Stochastic beams and where to find them: The gumbel-top-k trick for sampling sequences without replacement
W Kool, H Van Hoof, M Welling
International Conference on Machine Learning, 3499-3508, 2019
552019
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
522016
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
432014
Maximally Informative Interaction Learning for Scene Exploration
H van Hoof, O Kroemer, HB Amor, J Peters
Intelligent Robots and Systems, 2012
422012
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
392015
An inference-based policy gradient method for learning options
M Smith, H Hoof, J Pineau
International Conference on Machine Learning, 4703-4712, 2018
202018
Attention solves your TSP, approximately
W Kool, H van Hoof, M Welling
stat 1050, 22, 2018
202018
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
182014
Estimating Gradients for Discrete Random Variables by Sampling without Replacement
W Kool, H van Hoof, M Welling
arXiv preprint arXiv:2002.06043, 2020
172020
Non-parametric policy search with limited information loss
H Van Hoof, G Neumann, J Peters
Journal of Machine Learning Research 18 (73), 1-46, 2017
172017
Deep generative modeling of LiDAR data
L Caccia, H Van Hoof, A Courville, J Pineau
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2019
142019
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