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More Powerful Selective Kernel Tests for Feature Selection

Lim, J. N., Yamada, M., Jitkrittum, W., Terada, Y., Matsui, S., Shimodaira, H.

2019 (misc) Submitted

arXiv [BibTex]

arXiv [BibTex]


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Special Issue on Causal Discovery and Inference

Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J.

ACM Transactions on Intelligent Systems and Technology (TIST), 7(2), January 2016, (Guest Editors) (misc)

[BibTex]

[BibTex]


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Empirical Inference (2010-2015)
Scientific Advisory Board Report, 2016 (misc)

pdf [BibTex]

pdf [BibTex]


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Unsupervised Domain Adaptation in the Wild : Dealing with Asymmetric Label Set

Mittal, A., Raj, A., Namboodiri, V. P., Tuytelaars, T.

2016 (misc)

Arxiv [BibTex]


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Analysis of multiparametric MRI using a semi-supervised random forest framework allows the detection of therapy response in ischemic stroke

Castaneda, S., Katiyar, P., Russo, F., Calaminus, C., Disselhorst, J. A., Ziemann, U., Kohlhofer, U., Quintanilla-Martinez, L., Poli, S., Pichler, B. J.

World Molecular Imaging Conference, 2016 (talk)

link (url) [BibTex]

link (url) [BibTex]


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Screening Rules for Convex Problems

Raj, A., Olbrich, J., Gärtner, B., Schölkopf, B., Jaggi, M.

2016 (unpublished) Submitted

[BibTex]

[BibTex]


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Multi-view learning on multiparametric PET/MRI quantifies intratumoral heterogeneity and determines therapy efficacy

Katiyar, P., Divine, M. R., Kohlhofer, U., Quintanilla-Martinez, L., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J., Disselhorst, J. A.

World Molecular Imaging Conference, 2016 (talk)

link (url) [BibTex]

link (url) [BibTex]