| Compression of weighted graphs H Toivonen, F Zhou, A Hartikainen, A Hinkka Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 184 | 2011 |
| Predicting the geographical origin of music F Zhou, Q Claire, RD King 2014 IEEE International Conference on Data Mining, 1115-1120, 2014 | 75 | 2014 |
| Network simplification with minimal loss of connectivity F Zhou, S Malher, H Toivonen 2010 IEEE international conference on data mining, 659-668, 2010 | 70 | 2010 |
| Simplification of networks by edge pruning F Zhou, S Mahler, H Toivonen Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms …, 2012 | 40 | 2012 |
| A framework for path-oriented network simplification H Toivonen, S Mahler, F Zhou Advances in Intelligent Data Analysis IX: 9th International Symposium, IDA …, 2010 | 38 | 2010 |
| Graph compression F Zhou Department of Computer Science and Helsinki Institute for Information …, 2015 | 19 | 2015 |
| Summarisation of weighted networks F Zhou, Q Qu, H Toivonen Journal of Experimental & Theoretical Artificial Intelligence 29 (5), 1023-1052, 2017 | 17 | 2017 |
| Generalization-Aware Structured Regression towards Balancing Bias and Variance. M Pavlovski, F Zhou, N Arsov, L Kocarev, Z Obradovic IJCAI, 2616-2622, 2018 | 13 | 2018 |
| Gaussian conditional random fields extended for directed graphs T Vujicic, J Glass, F Zhou, Z Obradovic Machine Learning 106, 1271-1288, 2017 | 12 | 2017 |
| Network compression by node and edge mergers H Toivonen, F Zhou, A Hartikainen, A Hinkka Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms …, 2012 | 12 | 2012 |
| Fusing web and audio predictors to localize the origin of music pieces for geospatial retrieval M Schedl, F Zhou Advances in Information Retrieval: 38th European Conference on IR Research …, 2016 | 10 | 2016 |
| Adaptive Skip-Train Structured Regression for Temporal Networks M Pavlovski, F Zhou, I Stojkovic, L Kocarev, Z Obradovic ECML-PKDD 45, S45, 2017 | 9 | 2017 |
| Use of Disease Embedding Technique to Predict the Risk of Progression to End-Stage Renal Disease F Zhou, A Gillespie, D Gligorijevic, J Gligorijevic, Z Obradovic Journal of Biomedical Informatics, 103409, 2020 | 8 | 2020 |
| Leveraging subsequence-orders for univariate and multivariate time-series classification S Roychoudhury, F Zhou, Z Obradovic Proceedings of the 2019 SIAM International Conference on Data Mining, 495-503, 2019 | 8 | 2019 |
| A robust descriptor for color texture classification under varying illumination T Negri, F Zhou, Z Obradovic, A Gonzaga International Conference on Computer Vision Theory and Applications 5, 378-388, 2017 | 8 | 2017 |
| The use of weighted graphs for large-scale genome analysis F Zhou, H Toivonen, RD King PloS One 9 (3), e89618, 2014 | 8 | 2014 |
| Review of bisonet abstraction techniques F Zhou, S Mahler, H Toivonen Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms …, 2012 | 8 | 2012 |
| Dynamic self-paced sampling ensemble for highly imbalanced and class-overlapped data classification F Zhou, S Gao, L Ni, M Pavlovski, Q Dong, Z Obradovic, W Qian Data Mining and Knowledge Discovery 36 (5), 1601-1622, 2022 | 7 | 2022 |
| Review of network abstraction techniques F Zhou, S Mahler, H Toivonen Workshop on Explorative Analytics of Information Networks at ECML PKDD, 50-63, 2009 | 7 | 2009 |
| Predicting poll trends using twitter and multivariate time-series classification T Mirowski, S Roychoudhury, F Zhou, Z Obradovic Social Informatics: 8th International Conference, SocInfo 2016, Bellevue, WA …, 2016 | 6 | 2016 |
Hannu (TT) ToivonenProfessor of Computer Science, University of HelsinkiVerified email at helsinki.fi
