Herke van Hoof

5.2k total citations
36 papers, 1.0k citations indexed

About

Herke van Hoof is a scholar working on Artificial Intelligence, Control and Systems Engineering and Management Science and Operations Research. According to data from OpenAlex, Herke van Hoof has authored 36 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 7 papers in Control and Systems Engineering and 6 papers in Management Science and Operations Research. Recurrent topics in Herke van Hoof's work include Reinforcement Learning in Robotics (17 papers), Robot Manipulation and Learning (6 papers) and Advanced Bandit Algorithms Research (6 papers). Herke van Hoof is often cited by papers focused on Reinforcement Learning in Robotics (17 papers), Robot Manipulation and Learning (6 papers) and Advanced Bandit Algorithms Research (6 papers). Herke van Hoof collaborates with scholars based in Netherlands, Germany and Canada. Herke van Hoof's co-authors include Jan Peters, Gerhard Neumann, Tucker Hermans, Scott Fujimoto, David Meger, Oliver Kroemer, Wouter Kool, Max Welling, Christian Daniel and Filipe Veiga and has published in prestigious journals such as International Journal of Environmental Research and Public Health, Machine Learning and IEEE Transactions on Robotics.

In The Last Decade

Herke van Hoof

34 papers receiving 987 citations

Peers

Countries citing papers authored by Herke van Hoof

Since Specialization

Citations

This map shows the geographic impact of Herke van Hoof's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Herke van Hoof with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Herke van Hoof more than expected).

Fields of papers citing papers by Herke van Hoof

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Herke van Hoof. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Herke van Hoof. The network helps show where Herke van Hoof may publish in the future.

Co-authorship network of co-authors of Herke van Hoof

This figure shows the co-authorship network connecting the top 25 collaborators of Herke van Hoof. A scholar is included among the top collaborators of Herke van Hoof based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Herke van Hoof. Herke van Hoof is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Going Beyond Popularity and Positivity Bias: Correcting for Multifactorial Bias in Recommender Systems 2024 ·UvA-DARE (University of Amsterdam) ·(unknown), Harrie Oosterhuis, Masoud Mansoury, Herke van Hoof, Maarten de Rijke	3
2	Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits 2024 ·UvA-DARE (University of Amsterdam) ·Masoud Mansoury, Bamshad Mobasher, Herke van Hoof	0
3	Fast and Data Efficient Reinforcement Learning from Pixels via Non-parametric Value Approximation 2022 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Alexander Long, Alan Blair, Herke van Hoof	1
4	Reliably Re-Acting to Partner’s Actions with the Social Intrinsic Motivation of Transfer Empowerment 2022 ·(unknown), Herke van Hoof, Efstratios Gavves, Christoph Salge	0
5	Optimizing Adaptive Notifications in Mobile Health Interventions Systems: Reinforcement Learning from a Data-driven Behavioral Simulator 2021 ·Journal of Medical Systems ·Shihan Wang, Chao Zhang, Ben Kröse, Herke van Hoof	20
6	Ancestral Gumbel-Top-k Sampling for Sampling Without Replacement 2020 ·Journal of Machine Learning Research ·Wouter Kool, Herke van Hoof, Max Welling	11
7	A Performance-Based Start State Curriculum Framework for Reinforcement Learning 2020 ·UvA-DARE (University of Amsterdam) ·(unknown), (unknown), Herke van Hoof	4
8	Estimating Gradients for Discrete Random Variables by Sampling without Replacement 2020 ·arXiv (Cornell University) ·Wouter Kool, Herke van Hoof, Max Welling	4
9	Buy 4 REINFORCE Samples, Get a Baseline for Free! 2019 ·International Conference on Learning Representations ·Wouter Kool, Herke van Hoof, Max Welling	7
10	An inference-based policy gradient method for learning options 2018 ·UvA-DARE (University of Amsterdam) ·Matthew J. Smith, Herke van Hoof, Joëlle Pineau	4
11	Addressing Function Approximation Error in Actor-Critic Methods 2018 ·UvA-DARE (University of Amsterdam) ·Scott Fujimoto, Herke van Hoof, David Meger	143
12	Attention Solves Your TSP, Approximately 2018 ·arXiv (Cornell University) ·Wouter Kool, Herke van Hoof, Max Welling	11
13	Attention, Learn to Solve Routing Problems! 2018 ·UvA-DARE (University of Amsterdam) ·Wouter Kool, Herke van Hoof, Max Welling	77
14	Non-parametric policy search with limited information loss 2017 ·Journal of Machine Learning Research ·Herke van Hoof, Gerhard Neumann, Jan Peters	17
15	Generalized exploration in policy search 2017 ·Machine Learning ·Herke van Hoof, (unknown), Jan Peters	5
16	Probabilistic inference for determining options in reinforcement learning 2016 ·Machine Learning ·Christian Daniel, Herke van Hoof, Jan Peters, Gerhard Neumann	45
17	Learning of non-parametric control policies with high-dimensional state features 2015 ·Lincoln Repository (University of Lincoln) ·Herke van Hoof, Jan Peters, Gerhard Neumann	20
18	Towards learning hierarchical skills for multi-phase manipulation tasks 2015 ·Lincoln Repository (University of Lincoln) ·Oliver Kroemer, Christian Daniel, Gerhard Neumann, Herke van Hoof, Jan Peters	68
19	Learning to predict phases of manipulation tasks as hidden states 2014 ·Lincoln Repository (University of Lincoln) ·Oliver Kroemer, Herke van Hoof, Gerhard Neumann, Jan Peters	32
20	Probabilistic interactive segmentation for anthropomorphic robots in cluttered environments 2013 ·Herke van Hoof, Oliver Kroemer, Jan Peters	5

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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