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Liyuan Xu
Liyuan Xu
Verified email at ms.k.u-tokyo.ac.jp
Title
Cited by
Cited by
Year
A fully adaptive algorithm for pure exploration in linear bandits
L Xu, J Honda, M Sugiyama
International Conference on Artificial Intelligence and Statistics, 843-851, 2018
922018
Learning deep features in instrumental variable regression
L Xu, Y Chen, S Srinivasan, N de Freitas, A Doucet, A Gretton
arXiv preprint arXiv:2010.07154, 2020
562020
Deep proxy causal learning and its application to confounded bandit policy evaluation
L Xu, H Kanagawa, A Gretton
Advances in Neural Information Processing Systems 34, 26264-26275, 2021
342021
Kernel methods for causal functions: dose, heterogeneous and incremental response curves
R Singh, L Xu, A Gretton
Biometrika, asad042, 2023
182023
Kernel methods for multistage causal inference: Mediation analysis and dynamic treatment effects
R Singh, L Xu, A Gretton
arXiv preprint arXiv:2111.03950, 2021
162021
Polynomial-time algorithms for multiple-arm identification with full-bandit feedback
Y Kuroki, L Xu, A Miyauchi, J Honda, M Sugiyama
Neural Computation 32 (9), 1733-1773, 2020
162020
Similarity-based classification: Connecting similarity learning to binary classification
H Bao, T Shimada, L Xu, I Sato, M Sugiyama
arXiv preprint arXiv:2006.06207, 2020
142020
Uncoupled regression from pairwise comparison data
L Xu, J Honda, G Niu, M Sugiyama
Advances in Neural Information Processing Systems 32, 2019
132019
Alternate estimation of a classifier and the class-prior from positive and unlabeled data
M Kato, L Xu, G Niu, M Sugiyama
arXiv preprint arXiv:1809.05710, 2018
132018
On instrumental variable regression for deep offline policy evaluation
Y Chen, L Xu, C Gulcehre, T Le Paine, A Gretton, N De Freitas, A Doucet
Journal of Machine Learning Research 23 (302), 1-40, 2022
122022
Pairwise supervision can provably elicit a decision boundary
H Bao, T Shimada, L Xu, I Sato, M Sugiyama
arXiv preprint arXiv:2006.06207, 2020
102020
Kernel methods for policy evaluation: Treatment effects, mediation analysis, and off-policy planning
R Singh, L Xu, A Gretton
arXiv preprint arXiv:2010.04855 725, 2020
102020
Reproducing kernel methods for nonparametric and semiparametric treatment effects
R Singh, L Xu, A Gretton
arXiv preprint arXiv:2010.04855, 2020
72020
Polynomial-time algorithms for combinatorial pure exploration with full-bandit feedback
Y Kuroki, L Xu, A Miyauchi, J Honda, M Sugiyama
arXiv preprint arXiv:1902.10582, 2019
52019
Dueling bandits with qualitative feedback
L Xu, J Honda, M Sugiyama
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5549-5556, 2019
42019
Importance weighted kernel Bayesf rule
L Xu, Y Chen, A Doucet, A Gretton
International Conference on Machine Learning, 24524-24538, 2022
32022
Generalized kernel ridge regression for nonparametric structural functions and semiparametric treatment effects
R Singh, L Xu, A Gretton
arXiv preprint arXiv:2010.04855, 2020
32020
A neural mean embedding approach for back-door and front-door adjustment
L Xu, A Gretton
arXiv preprint arXiv:2210.06610, 2022
22022
Importance Weighting Approach in Kernel Bayes' Rule
L Xu, Y Chen, A Doucet, A Gretton
arXiv preprint arXiv:2202.02474, 2022
12022
Kernel Single Proxy Control for Deterministic Confounding
L Xu, A Gretton
arXiv preprint arXiv:2308.04585, 2023
2023
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