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2011.08541
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Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization
Neural Information Processing Systems (NeurIPS), 2020
17 November 2020
Sreejith Balakrishnan
Q. Nguyen
Bryan Kian Hsiang Low
Harold Soh
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Papers citing
"Efficient Exploration of Reward Functions in Inverse Reinforcement Learning via Bayesian Optimization"
17 / 17 papers shown
Embracing Evolution: A Call for Body-Control Co-Design in Embodied Humanoid Robot
Guiliang Liu
Bo Yue
Yi Jin Kim
Kui Jia
191
1
0
03 Oct 2025
Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
Bo Yue
Jian Li
Guiliang Liu
485
3
0
24 Sep 2024
A Generalized Acquisition Function for Preference-based Reward Learning
IEEE International Conference on Robotics and Automation (ICRA), 2024
Evan Ellis
Gaurav R. Ghosal
Stuart J. Russell
Anca Dragan
Erdem Biyik
299
7
0
09 Mar 2024
Inverse Decision Modeling: Learning Interpretable Representations of Behavior
International Conference on Machine Learning (ICML), 2023
Daniel Jarrett
Alihan Huyuk
M. Schaar
AI4CE
266
30
0
28 Oct 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
International Conference on Machine Learning (ICML), 2023
Apivich Hemachandra
Zhongxiang Dai
Jasraj Singh
See-Kiong Ng
K. H. Low
AAML
298
8
0
07 Jun 2023
Reward Learning with Intractable Normalizing Functions
IEEE Robotics and Automation Letters (RA-L), 2023
Joshua Hoegerman
Dylan P. Losey
233
2
0
16 May 2023
Kernel Density Bayesian Inverse Reinforcement Learning
Aishwarya Mandyam
Didong Li
Jiayu Yao
Diana Cai
Andrew Jones
Barbara E. Engelhardt
OffRL
BDL
558
3
0
13 Mar 2023
Active Learning and Bayesian Optimization: a Unified Perspective to Learn with a Goal
Archives of Computational Methods in Engineering (ACME), 2023
Francesco Di Fiore
Michela Nardelli
L. Mainini
454
64
0
02 Mar 2023
Sample-Then-Optimize Batch Neural Thompson Sampling
Neural Information Processing Systems (NeurIPS), 2022
Zhongxiang Dai
Yao Shu
Bryan Kian Hsiang Low
Patrick Jaillet
AAML
229
30
0
13 Oct 2022
Identifiability and generalizability from multiple experts in Inverse Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2022
Paul Rolland
Luca Viano
Norman Schuerhoff
Boris Nikolov
Volkan Cevher
OffRL
370
19
0
22 Sep 2022
Bayesian Optimization under Stochastic Delayed Feedback
International Conference on Machine Learning (ICML), 2022
Arun Verma
Zhongxiang Dai
Bryan Kian Hsiang Low
256
15
0
19 Jun 2022
Modeling Human Behavior Part I -- Learning and Belief Approaches
Andrew Fuchs
A. Passarella
M. Conti
297
8
0
13 May 2022
Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Hung The Tran
Sunil R. Gupta
Santu Rana
Svetha Venkatesh
223
18
0
15 Mar 2022
MIRROR: Differentiable Deep Social Projection for Assistive Human-Robot Communication
Kaiqi Chen
J. Fong
Harold Soh
218
10
0
06 Mar 2022
Differentially Private Federated Bayesian Optimization with Distributed Exploration
Zhongxiang Dai
K. H. Low
Patrick Jaillet
FedML
231
60
0
27 Oct 2021
Inverse Contextual Bandits: Learning How Behavior Evolves over Time
Alihan Huyuk
Daniel Jarrett
M. Schaar
CML
OffRL
386
13
0
13 Jul 2021
Identifiability in inverse reinforcement learning
Neural Information Processing Systems (NeurIPS), 2021
Haoyang Cao
Samuel N. Cohen
Lukasz Szpruch
412
58
0
07 Jun 2021
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