Kun Zhang
Kun Zhang
Carnegie Mellon University & Max-Planck Institute for Intelligent Systems
Verified email at cmu.edu - Homepage
TitleCited byYear
Multi-label learning by exploiting label dependency
ML Zhang, K Zhang
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
Kernel-based conditional independence test and application in causal discovery
K Zhang, J Peters, D Janzing, B Schölkopf
arXiv preprint arXiv:1202.3775, 2012
On the identifiability of the post-nonlinear causal model
K Zhang, A Hyvärinen
Proceedings of the twenty-fifth conference on uncertainty in artificial …, 2009
Domain adaptation under target and conditional shift
K Zhang, B Schölkopf, K Muandet, Z Wang
International Conference on Machine Learning, 819-827, 2013
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
On causal and anticausal learning
B Schölkopf, D Janzing, J Peters, E Sgouritsa, K Zhang, J Mooij
arXiv preprint arXiv:1206.6471, 2012
On causal and anticausal learning
B Schölkopf, D Janzing, J Peters, E Sgouritsa, K Zhang, J Mooij
arXiv preprint arXiv:1206.6471, 2012
Estimation of a structural vector autoregression model using non-gaussianity
A Hyvärinen, K Zhang, S Shimizu, PO Hoyer
Journal of Machine Learning Research 11 (May), 1709-1731, 2010
Inferring deterministic causal relations
P Daniusis, D Janzing, J Mooij, J Zscheischler, B Steudel, K Zhang, ...
arXiv preprint arXiv:1203.3475, 2012
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
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
Causal discovery and inference: concepts and recent methodological advances
P Spirtes, K Zhang
Applied informatics 3 (1), 3, 2016
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, 1687-1695, 2010
An adaptive method for subband decomposition ICA
K Zhang, LW Chan
Neural computation 18 (1), 191-223, 2006
Model selection for gaussian mixture models
T Huang, H Peng, K Zhang
arXiv preprint arXiv:1301.3558, 2013
Multi-source domain adaptation: A causal view
K Zhang, M Gong, B Schölkopf
Twenty-ninth AAAI conference on artificial intelligence, 2015
Symbol recognition with kernel density matching
W Zhang, L Wenyin, K Zhang
IEEE transactions on pattern analysis and machine intelligence 28 (12), 2020 …, 2006
Distinguishing causes from effects using nonlinear acyclic causal models
K Zhang, A Hyvärinen
Proceedings of the 2008th International Conference on Causality: Objectives …, 2008
A Permutation-Based Kernel Conditional Independence Test.
G Doran, K Muandet, K Zhang, B Schölkopf
UAI, 132-141, 2014
Causal inference by identification of vector autoregressive processes with hidden components
P Geiger, K Zhang, B Schoelkopf, M Gong, D Janzing
International Conference on Machine Learning, 1917-1925, 2015
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Articles 1–20