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Krikamol Muandet
Krikamol Muandet
CISPA - Helmholtz Center for Information Security
E-mail confirmado em cispa.de - Página inicial
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Citado por
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Ano
Domain generalization via invariant feature representation
K Muandet, D Balduzzi, B Schölkopf
International conference on machine learning, 10-18, 2013
13462013
Kernel mean embedding of distributions: A review and beyond
K Muandet, K Fukumizu, B Sriperumbudur, B Schölkopf
Foundations and Trends® in Machine Learning 10 (1-2), 1-141, 2017
9182017
Domain adaptation under target and conditional shift
K Zhang, B Schölkopf, K Muandet, Z Wang
International conference on machine learning, 819-827, 2013
7832013
Learning from distributions via support measure machines
K Muandet, K Fukumizu, F Dinuzzo, B Schölkopf
Advances in neural information processing systems 25, 2012
2382012
Grasping field: Learning implicit representations for human grasps
K Karunratanakul, J Yang, Y Zhang, MJ Black, K Muandet, S Tang
2020 International Conference on 3D Vision (3DV), 333-344, 2020
2242020
Towards a learning theory of cause-effect inference
D Lopez-Paz, K Muandet, B Schölkopf, I Tolstikhin
International Conference on Machine Learning, 1452-1461, 2015
2232015
A Permutation-Based Kernel Conditional Independence Test.
G Doran, K Muandet, K Zhang, B Schölkopf
UAI, 132-141, 2014
1622014
Eigendecompositions of transfer operators in reproducing kernel Hilbert spaces
S Klus, I Schuster, K Muandet
Journal of Nonlinear Science 30, 283-315, 2020
1482020
Design and analysis of the NIPS 2016 review process
NB Shah, B Tabibian, K Muandet, I Guyon, U Von Luxburg
Journal of machine learning research 19 (49), 1-34, 2018
1202018
One-class support measure machines for group anomaly detection
K Muandet, B Schölkopf
arXiv preprint arXiv:1303.0309, 2013
1142013
Dual instrumental variable regression
K Muandet, A Mehrjou, SK Lee, A Raj
Advances in Neural Information Processing Systems 33, 2710-2721, 2020
1102020
A measure-theoretic approach to kernel conditional mean embeddings
J Park, K Muandet
Advances in neural information processing systems 33, 21247-21259, 2020
992020
Minimax estimation of kernel mean embeddings
I Tolstikhin, BK Sriperumbudur, K Mu
Journal of Machine Learning Research 18 (86), 1-47, 2017
842017
Proximal causal learning with kernels: Two-stage estimation and moment restriction
A Mastouri, Y Zhu, L Gultchin, A Korba, R Silva, M Kusner, A Gretton, ...
International conference on machine learning, 7512-7523, 2021
722021
Fair decisions despite imperfect predictions
N Kilbertus, MG Rodriguez, B Schölkopf, K Muandet, I Valera
International Conference on Artificial Intelligence and Statistics, 277-287, 2020
682020
Regularization, optimization, kernels, and support vector machines
JAK Suykens, M Signoretto, A Argyriou
CRC Press, 2014
662014
Kernel mean shrinkage estimators
K Mu, B Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf
Journal of Machine Learning Research 17 (48), 1-41, 2016
612016
Empirical inference: Festschrift in honor of Vladimir N. Vapnik
B Schölkopf, Z Luo, V Vovk
Springer Science & Business Media, 2013
542013
Kernel mean estimation and Stein effect
K Muandet, K Fukumizu, B Sriperumbudur, A Gretton, B Schölkopf
International Conference on Machine Learning, 10-18, 2014
502014
Counterfactual mean embeddings
K Muandet, M Kanagawa, S Saengkyongam, S Marukatat
Journal of Machine Learning Research 22 (162), 1-71, 2021
452021
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