| Synchronization-inspired partitioning and hierarchical clustering J Shao, X He, C Böhm, Q Yang, C Plant IEEE Transactions on Knowledge and Data Engineering 25 (4), 893-905, 2012 | 62 | 2012 |
| Learning discrete structures for graph neural networks L Franceschi, M Niepert, M Pontil, X He International conference on machine learning, 1972-1982, 2019 | 52 | 2019 |
| Anytime density-based clustering of complex data ST Mai, X He, J Feng, C Plant, C Böhm Knowledge and Information Systems 45 (2), 319-355, 2015 | 35 | 2015 |
| Efficient anytime density-based clustering ST Mai, X He, J Feng, C Böhm Proceedings of the 2013 SIAM International Conference on Data Mining, 112-120, 2013 | 30 | 2013 |
| Active density-based clustering ST Mai, X He, N Hubig, C Plant, C Böhm 2013 IEEE 13th International Conference on Data Mining, 508-517, 2013 | 29 | 2013 |
| Summarization-based mining bipartite graphs J Feng, X He, B Konte, C Böhm, C Plant Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 24 | 2012 |
| Kernelized rank learning for personalized drug recommendation X He, L Folkman, K Borgwardt Bioinformatics, 2018 | 23 | 2018 |
| Finding the optimal subspace for clustering S Goebl, X He, C Plant, C Böhm 2014 IEEE International Conference on Data Mining, 130-139, 2014 | 18 | 2014 |
| Robust synchronization-based graph clustering J Shao, X He, Q Yang, C Plant, C Böhm Pacific-Asia conference on knowledge discovery and data mining, 249-260, 2013 | 15 | 2013 |
| Relevant overlapping subspace clusters on categorical data X He, J Feng, B Konte, ST Mai, C Plant Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 13 | 2014 |
| Compression-based graph mining exploiting structure primitives J Feng, X He, N Hubig, C Böhm, C Plant 2013 IEEE 13th International Conference on Data Mining, 181-190, 2013 | 12 | 2013 |
| A novel similarity measure for fiber clustering using longest common subsequence C Böhm, J Feng, X He, ST Mai, C Plant, J Shao Proceedings of the 2011 workshop on data mining for medicine and healthcare, 1-9, 2011 | 10 | 2011 |
| Multi-target drug repositioning by bipartite block-wise sparse multi-task learning L Li, X He, K Borgwardt BMC systems biology 12 (4), 85-97, 2018 | 7 | 2018 |
| Multi-view spectral clustering on conflicting views X He, L Li, D Roqueiro, K Borgwardt Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017 | 7 | 2017 |
| Efficient and scalable multi-task regression on massive number of tasks X He, F Alesiani, A Shaker Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 3763-3770, 2019 | 5 | 2019 |
| Kernel Conditional Clustering X He, T Gumbsch, D Roqueiro, K Borgwardt IEEE International Conference on Data Mining (ICDM), 157-166, 2017 | 3 | 2017 |
| Multi-purpose exploratory mining of complex data X He lmu, 2014 | 3 | 2014 |
| Robust continuous co-clustering X He, L Moreira-Matias arXiv preprint arXiv:1802.05036, 2018 | 2 | 2018 |
| Kernel conditional clustering and kernel conditional semi-supervised learning X He, T Gumbsch, D Roqueiro, K Borgwardt Knowledge and information systems, 1-27, 2019 | 1 | 2019 |
| Automatically spotting information-rich nodes in graphs X He, J Feng, C Plant 2011 IEEE 11th International Conference on Data Mining Workshops, 941-948, 2011 | 1 | 2011 |
Claudia PlantProfessor of Computer Science, research group Data Mining and Machine Learning, UniVieVerified email at univie.ac.at
