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1206.4655
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Modelling transition dynamics in MDPs with RKHS embeddings
International Conference on Machine Learning (ICML), 2012
18 June 2012
Steffen Grunewalder
Guy Lever
Luca Baldassarre
Massimiliano Pontil
Arthur Gretton
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Papers citing
"Modelling transition dynamics in MDPs with RKHS embeddings"
50 / 50 papers shown
Sampling Complexity of TD and PPO in RKHS
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Operator World Models for Reinforcement Learning
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379
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Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering
Yuki Akiyama
Minh Vu
Konstantinos Slavakis
292
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29 Mar 2024
Distributional Bellman Operators over Mean Embeddings
International Conference on Machine Learning (ICML), 2023
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Grégoire Delétang
Matthew Aitchison
Marcus Hutter
Anian Ruoss
Arthur Gretton
Mark Rowland
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301
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09 Dec 2023
Proximal Bellman mappings for reinforcement learning and their application to robust adaptive filtering
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023
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Konstantinos Slavakis
230
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14 Sep 2023
Bayesian Exploration Networks
International Conference on Machine Learning (ICML), 2023
Matt Fellows
Brandon Kaplowitz
Christian Schroeder de Witt
Shimon Whiteson
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519
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24 Aug 2023
Stochastic Nonlinear Control via Finite-dimensional Spectral Dynamic Embedding
IEEE Conference on Decision and Control (CDC), 2023
Zhaolin Ren
Tongzheng Ren
Haitong Ma
Na Li
Bo Dai
382
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08 Apr 2023
Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models
IEEE International Conference on Robotics and Automation (ICRA), 2023
Yi Liu
Gaurav Datta
Ellen R. Novoseller
Daniel S. Brown
345
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11 Jan 2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control
American Control Conference (ACC), 2023
Adam J. Thorpe
Cyrus Neary
Franck Djeumou
Meeko Oishi
Ufuk Topcu
339
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09 Jan 2023
Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation
Diego Martinez-Taboada
Dino Sejdinovic
CML
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173
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02 Nov 2022
Sequential Decision Making on Unmatched Data using Bayesian Kernel Embeddings
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Dino Sejdinovic
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181
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25 Oct 2022
Statistical Estimation of Confounded Linear MDPs: An Instrumental Variable Approach
Miao Lu
Wenhao Yang
Liangyu Zhang
Zhihua Zhang
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249
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12 Sep 2022
Optimal Rates for Regularized Conditional Mean Embedding Learning
Neural Information Processing Systems (NeurIPS), 2022
Zhu Li
Dimitri Meunier
Mattes Mollenhauer
Arthur Gretton
376
65
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02 Aug 2022
Illusory Attacks: Information-Theoretic Detectability Matters in Adversarial Attacks
International Conference on Learning Representations (ICLR), 2022
Tim Franzmeyer
Stephen McAleer
João F. Henriques
Jakob N. Foerster
Juil Sock
Adel Bibi
Christian Schroeder de Witt
AAML
368
12
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20 Jul 2022
The Sufficiency of Off-Policyness and Soft Clipping: PPO is still Insufficient according to an Off-Policy Measure
AAAI Conference on Artificial Intelligence (AAAI), 2022
Xing Chen
Dongcui Diao
Hechang Chen
Hengshuai Yao
Haiyin Piao
Zhixiao Sun
Zhiwei Yang
Randy Goebel
Bei Jiang
Yi-Ju Chang
OffRL
553
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20 May 2022
Approximate discounting-free policy evaluation from transient and recurrent states
Vektor Dewanto
M. Gallagher
OffRL
99
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08 Apr 2022
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods
International Conference on Hybrid Systems: Computation and Control (HSCC), 2022
Adam J. Thorpe
Meeko Oishi
134
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12 Mar 2022
Optimal policy evaluation using kernel-based temporal difference methods
Annals of Statistics (Ann. Stat.), 2021
Yaqi Duan
Mengdi Wang
Martin J. Wainwright
OffRL
256
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24 Sep 2021
Sobolev Norm Learning Rates for Conditional Mean Embeddings
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Prem M. Talwai
A. Shameli
D. Simchi-Levi
354
12
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16 May 2021
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction
International Conference on Machine Learning (ICML), 2021
Afsaneh Mastouri
Yuchen Zhu
Limor Gultchin
Anna Korba
Ricardo M. A. Silva
Matt J. Kusner
Arthur Gretton
Krikamol Muandet
CML
676
78
0
10 May 2021
Towards Theoretical Understandings of Robust Markov Decision Processes: Sample Complexity and Asymptotics
Wenhao Yang
Liangyu Zhang
Zhihua Zhang
304
35
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09 May 2021
Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks
Thanh Nguyen-Tang
Sunil R. Gupta
Hung The Tran
Svetha Venkatesh
OffRL
508
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11 Mar 2021
Online Learning for Unknown Partially Observable MDPs
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Mehdi Jafarnia-Jahromi
Rahul Jain
A. Nayyar
338
24
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25 Feb 2021
Accountable Off-Policy Evaluation With Kernel Bellman Statistics
Yihao Feng
Zhaolin Ren
Ziyang Tang
Qiang Liu
OffRL
294
45
0
15 Aug 2020
Kernel Autocovariance Operators of Stationary Processes: Estimation and Convergence
Journal of machine learning research (JMLR), 2020
Mattes Mollenhauer
Stefan Klus
Christof Schütte
P. Koltai
276
11
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02 Apr 2020
Minimax-Optimal Off-Policy Evaluation with Linear Function Approximation
International Conference on Machine Learning (ICML), 2020
Yaqi Duan
Mengdi Wang
OffRL
330
160
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21 Feb 2020
Frequency-based Search-control in Dyna
International Conference on Learning Representations (ICLR), 2020
Yangchen Pan
Jincheng Mei
Amir-massoud Farahmand
163
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14 Feb 2020
A Measure-Theoretic Approach to Kernel Conditional Mean Embeddings
Neural Information Processing Systems (NeurIPS), 2020
Junhyung Park
Krikamol Muandet
699
116
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10 Feb 2020
A New Distribution-Free Concept for Representing, Comparing, and Propagating Uncertainty in Dynamical Systems with Kernel Probabilistic Programming
IFAC-PapersOnLine (IFAC-PapersOnLine), 2019
Jia Jie Zhu
Krikamol Muandet
Moritz Diehl
Bernhard Schölkopf
244
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25 Nov 2019
Learning low-dimensional state embeddings and metastable clusters from time series data
Neural Information Processing Systems (NeurIPS), 2019
Yifan Sun
Yaqi Duan
Hao Gong
Mengdi Wang
AI4TS
232
19
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01 Jun 2019
Kernel Instrumental Variable Regression
Neural Information Processing Systems (NeurIPS), 2019
Rahul Singh
M. Sahani
Arthur Gretton
820
197
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01 Jun 2019
Organizing Experience: A Deeper Look at Replay Mechanisms for Sample-based Planning in Continuous State Domains
Yangchen Pan
M. Zaheer
Adam White
Andrew Patterson
Martha White
340
49
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12 Jun 2018
Nonparametric Stochastic Compositional Gradient Descent for Q-Learning in Continuous Markov Decision Problems
American Control Conference (ACC), 2018
Alec Koppel
Ekaterina V. Tolstaya
Ethan Stump
Alejandro Ribeiro
148
22
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19 Apr 2018
Practical Issues of Action-conditioned Next Image Prediction
Donglai Zhu
Hao Chen
Hengshuai Yao
M. Nosrati
Peyman Yadmellat
Yunfei Zhang
168
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08 Feb 2018
Barrier-Certified Adaptive Reinforcement Learning with Applications to Brushbot Navigation
Motoya Ohnishi
Li Wang
Gennaro Notomista
M. Egerstedt
346
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29 Jan 2018
Learning from Conditional Distributions via Dual Embeddings
Bo Dai
Niao He
Yunpeng Pan
Byron Boots
Le Song
320
21
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15 Jul 2016
Kernel Bayesian Inference with Posterior Regularization
Neural Information Processing Systems (NeurIPS), 2016
Yang Song
Jun Zhu
Yong Ren
301
11
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07 Jul 2016
Difference of Convex Functions Programming Applied to Control with Expert Data
Bilal Piot
Matthieu Geist
Olivier Pietquin
OffRL
210
7
0
03 Jun 2016
Uncertain programming model for multi-item solid transportation problem
International Journal of Machine Learning and Cybernetics (IJMLC), 2016
Hasan Dalman
551
859
0
31 May 2016
Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models
Bernardo Avila-Pires
Csaba Szepesvári
OffRL
143
23
0
19 Feb 2016
Doubly Robust Off-policy Value Evaluation for Reinforcement Learning
Nan Jiang
Lihong Li
OffRL
608
693
0
11 Nov 2015
Model-based Kernel Sum Rule: Kernel Bayesian Inference with Probabilistic Models
Machine-mediated learning (ML), 2014
Yu Nishiyama
Motonobu Kanagawa
Arthur Gretton
Kenji Fukumizu
461
4
0
18 Sep 2014
Practical Kernel-Based Reinforcement Learning
Journal of machine learning research (JMLR), 2014
André Barreto
Doina Precup
Joelle Pineau
OffRL
227
48
0
21 Jul 2014
Characteristic Kernels and Infinitely Divisible Distributions
Journal of machine learning research (JMLR), 2014
Yu Nishiyama
Kenji Fukumizu
364
13
0
28 Mar 2014
Filtering with State-Observation Examples via Kernel Monte Carlo Filter
Neural Computation (Neural Comput.), 2013
Motonobu Kanagawa
Yu Nishiyama
Arthur Gretton
Kenji Fukumizu
411
22
0
17 Dec 2013
Hilbert Space Embeddings of Predictive State Representations
Conference on Uncertainty in Artificial Intelligence (UAI), 2013
Byron Boots
Geoffrey J. Gordon
Arthur Gretton
281
97
0
26 Sep 2013
Hilbert Space Embeddings of POMDPs
Conference on Uncertainty in Artificial Intelligence (UAI), 2012
Yu Nishiyama
Abdeslam Boularias
Arthur Gretton
Kenji Fukumizu
257
52
0
16 Oct 2012
Path Integral Control by Reproducing Kernel Hilbert Space Embedding
International Joint Conference on Artificial Intelligence (IJCAI), 2012
K. Rawlik
Marc Toussaint
S. Vijayakumar
438
27
0
13 Aug 2012
Conditional mean embeddings as regressors - supplementary
International Conference on Machine Learning (ICML), 2012
Steffen Grunewalder
Guy Lever
Luca Baldassarre
Sam Patterson
Arthur Gretton
Massimiliano Pontil
436
159
0
21 May 2012
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