Krikamol Muandet
Krikamol Muandet
Max Planck Institute for Intelligent Systems
Verified email at tuebingen.mpg.de - Homepage
Title
Cited by
Cited by
Year
Domain adaptation under target and conditional shift
K Zhang, B Schölkopf, K Muandet, Z Wang
International Conference on Machine Learning, 819-827, 2013
2762013
Domain generalization via invariant feature representation
K Muandet, D Balduzzi, B Schölkopf
International Conference on Machine Learning, 10-18, 2013
2662013
Kernel mean embedding of distributions: A review and beyond
K Muandet, K Fukumizu, B Sriperumbudur, B Schölkopf
arXiv preprint arXiv:1605.09522, 2016
2492016
Learning from distributions via support measure machines
K Muandet, K Fukumizu, F Dinuzzo, B Schölkopf
Advances in neural information processing systems, 10-18, 2012
1492012
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
1132015
One-class support measure machines for group anomaly detection
K Muandet, B Schölkopf
arXiv preprint arXiv:1303.0309, 2013
662013
A Permutation-Based Kernel Conditional Independence Test.
G Doran, K Muandet, K Zhang, B Schölkopf
UAI, 132-141, 2014
612014
Computing functions of random variables via reproducing kernel Hilbert space representations
B Schölkopf, K Muandet, K Fukumizu, S Harmeling, J Peters
Statistics and Computing 25 (4), 755-766, 2015
332015
Kernel mean shrinkage estimators
K Muandet, B Sriperumbudur, K Fukumizu, A Gretton, B Schölkopf
The Journal of Machine Learning Research 17 (1), 1656-1696, 2016
322016
Design and analysis of the nips 2016 review process
NB Shah, B Tabibian, K Muandet, I Guyon, U Von Luxburg
The Journal of Machine Learning Research 19 (1), 1913-1946, 2018
312018
Kernel mean estimation and stein effect
K Muandet, K Fukumizu, B Sriperumbudur, A Gretton, B Schölkopf
International Conference on Machine Learning, 10-18, 2014
302014
Minimax estimation of kernel mean embeddings
I Tolstikhin, BK Sriperumbudur, K Muandet
The Journal of Machine Learning Research 18 (1), 3002-3048, 2017
272017
Regularization, optimization, kernels, and support vector machines
JAK Suykens, M Signoretto, A Argyriou
CRC Press, 2014
272014
Eigendecompositions of transfer operators in reproducing kernel Hilbert spaces
S Klus, I Schuster, K Muandet
Journal of Nonlinear Science 30 (1), 283-315, 2020
242020
The randomized causation coefficient
D Lopez-Paz, K Muandet, B Recht
The Journal of Machine Learning Research 16 (1), 2901-2907, 2015
212015
Kernel mean estimation via spectral filtering
K Muandet, B Sriperumbudur, B Schölkopf
Advances in Neural Information Processing Systems, 1-9, 2014
122014
Tersesvm: A scalable approach for learning compact models in large-scale classification
R Babbar, K Maundet, B Schölkopf
Proceedings of the 2016 SIAM International Conference on Data Mining, 234-242, 2016
72016
Dual iv: A single stage instrumental variable regression
K Muandet, A Mehrjou, SK Lee, A Raj
arXiv preprint arXiv:1910.12358, 2019
62019
Quantum mean embedding of probability distributions
JM Kübler, K Muandet, B Schölkopf
Physical Review Research 1 (3), 033159, 2019
52019
Improving consequential decision making under imperfect predictions
N Kilbertus, M Gomez-Rodriguez, B Schölkopf, K Muandet, I Valera
arXiv preprint arXiv:1902.02979, 2019
42019
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Articles 1–20