Kun Zhang
Kun Zhang
Carnegie Mellon University & Max-Planck Institute for Intelligent Systems
Verified email at cmu.edu - Homepage
Title
Cited by
Cited by
Year
Multi-label learning by exploiting label dependency
ML Zhang, K Zhang
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
4482010
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
3792018
Domain adaptation under target and conditional shift
K Zhang, B Schölkopf, K Muandet, Z Wang
International Conference on Machine Learning, 819-827, 2013
3232013
Kernel-based conditional independence test and application in causal discovery
K Zhang, J Peters, D Janzing, B Schölkopf
arXiv preprint arXiv:1202.3775, 2012
3182012
On the identifiability of the post-nonlinear causal model
K Zhang, A Hyvarinen
arXiv preprint arXiv:1205.2599, 2012
2872012
On causal and anticausal learning
B Schölkopf, D Janzing, J Peters, E Sgouritsa, K Zhang, J Mooij
arXiv preprint arXiv:1206.6471, 2012
2342012
On causal and anticausal learning
B Schölkopf, D Janzing, J Peters, E Sgouritsa, K Zhang, J Mooij
arXiv preprint arXiv:1206.6471, 2012
2342012
Information-geometric approach to inferring causal directions
D Janzing, J Mooij, K Zhang, J Lemeire, J Zscheischler, P Daniušis, ...
Artificial Intelligence 182, 1-31, 2012
2102012
Estimation of a structural vector autoregression model using non-gaussianity.
A Hyvärinen, K Zhang, S Shimizu, PO Hoyer
Journal of Machine Learning Research 11 (5), 2010
1892010
Domain adaptation with conditional transferable components
M Gong, K Zhang, T Liu, D Tao, C Glymour, B Schölkopf
International conference on machine learning, 2839-2848, 2016
1722016
Causal discovery and inference: concepts and recent methodological advances
P Spirtes, K Zhang
Applied informatics 3 (1), 3, 2016
1492016
Inferring deterministic causal relations
P Daniusis, D Janzing, J Mooij, J Zscheischler, B Steudel, K Zhang, ...
arXiv preprint arXiv:1203.3475, 2012
1422012
Probabilistic latent variable models for distinguishing between cause and effect
O Stegle, D Janzing, K Zhang, JM Mooij, B Schölkopf
Advances in neural information processing systems 23, 1687-1695, 2010
1022010
Multi-source domain adaptation: A causal view
K Zhang, M Gong, B Schölkopf
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
992015
On learning invariant representation for domain adaptation
H Zhao, RT Combes, K Zhang, GJ Gordon
arXiv preprint arXiv:1901.09453, 2019
982019
Deep domain generalization via conditional invariant adversarial networks
Y Li, X Tian, M Gong, Y Liu, T Liu, K Zhang, D Tao
Proceedings of the European Conference on Computer Vision (ECCV), 624-639, 2018
952018
Inferring causation from time series in Earth system sciences
J Runge, S Bathiany, E Bollt, G Camps-Valls, D Coumou, E Deyle, ...
Nature communications 10 (1), 1-13, 2019
912019
Review of causal discovery methods based on graphical models
C Glymour, K Zhang, P Spirtes
Frontiers in genetics 10, 524, 2019
762019
Model selection for Gaussian mixture models
T Huang, H Peng, K Zhang
Statistica Sinica, 147-169, 2017
762017
Model selection for Gaussian mixture models
T Huang, H Peng, K Zhang
Statistica Sinica, 147-169, 2017
762017
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