| Outlier detection using replicator neural networks S Hawkins, H He, G Williams, R Baxter International Conference on Data Warehousing and Knowledge Discovery, 170-180, 2002 | 1057 | 2002 |
| On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms K Yamanishi, JI Takeuchi, G Williams, P Milne Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000 | 965 | 2000 |
| Autobiographical memory in depression: state or trait marker? AD Brittlebank, J Scott, J Mark, G Williams, IN Ferrier The British Journal of Psychiatry 162 (1), 118-121, 1993 | 687 | 1993 |
| Data mining with Rattle and R: The art of excavating data for knowledge discovery G Williams Springer Science & Business Media, 2011 | 682 | 2011 |
| Emergence of vancomycin-resistant enterococci in New York City TR Frieden, SS Munsiff, G Williams, Y Faur, B Kreiswirth, DE Low, ... The Lancet 342 (8863), 76-79, 1993 | 448 | 1993 |
| A comparative study of RNN for outlier detection in data mining G Williams, R Baxter, H He, S Hawkins, L Gu 2002 IEEE International Conference on Data Mining, 2002. Proceedings., 709-712, 2002 | 440 | 2002 |
| Big data opportunities and challenges: Discussions from data analytics perspectives [discussion forum] ZH Zhou, NV Chawla, Y Jin, GJ Williams IEEE Computational intelligence magazine 9 (4), 62-74, 2014 | 369 | 2014 |
| Rattle: a data mining GUI for R G Williams Copenhagen Business School Press, 2009 | 248 | 2009 |
| PMML: An open standard for sharing models. A Guazzelli, M Zeller, WC Lin, G Williams R J. 1 (1), 60, 2009 | 243 | 2009 |
| Topic oriented community detection through social objects and link analysis in social networks Z Zhao, S Feng, Q Wang, JZ Huang, GJ Williams, J Fan Knowledge-Based Systems 26, 164-173, 2012 | 222 | 2012 |
| Categoric and extended autobiographical memories J Mark, G Williams, BH Dritschel Theoretical perspectives on autobiographical memory, 391-410, 1992 | 214 | 1992 |
| Two organic fixatives for acid mucopolysaccharides G Williams, DS Jackson Stain Technology 31 (5), 189-191, 1956 | 197 | 1956 |
| The use of mindfulness-based approaches for suicidal patients J Mark, G Williams, M Swales Archives of suicide research 8 (4), 315-329, 2004 | 171 | 2004 |
| Cause of death and predictors of all‐cause mortality in anticoagulated patients with nonvalvular atrial fibrillation: data from ROCKET AF SD Pokorney, JP Piccini, SR Stevens, MR Patel, KS Pieper, JL Halperin, ... Journal of the American Heart Association 5 (3), e002197, 2016 | 163 | 2016 |
| Mining unexpected temporal associations: applications in detecting adverse drug reactions H Jin, J Chen, H He, GJ Williams, C Kelman, CM O'Keefe IEEE Transactions on Information Technology in Biomedicine 12 (4), 488-500, 2008 | 134 | 2008 |
| Mining the knowledge mine: The hot spots methodology for mining large real world databases GJ Williams, Z Huang Advanced Topics in Artificial Intelligence: 10th Australian Joint Conference …, 1997 | 134 | 1997 |
| Autobiographical memory and emotional disorders J Mark, G Williams The handbook of emotion and memory, 451-477, 2014 | 133 | 2014 |
| Mining risk patterns in medical data J Li, AW Fu, H He, J Chen, H Jin, D McAullay, G Williams, R Sparks, ... Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005 | 120 | 2005 |
| Classifying very high-dimensional data with random forests built from small subspaces B Xu, JZ Huang, G Williams, Q Wang, Y Ye International Journal of Data Warehousing and Mining (IJDWM) 8 (2), 44-63, 2012 | 109 | 2012 |
| An Overview Of Temporal Data Mining. W Lin, MA Orgun, GJ Williams AusDM, 83-90, 2002 | 106 | 2002 |
