Constrained k-means clustering with background knowledge K Wagstaff, C Cardie, S Rogers, S Schrödl Icml 1, 577-584, 2001 | 3920 | 2001 |
Clustering with instance-level constraints K Wagstaff, C Cardie AAAI/IAAI 1097 (577-584), 197, 2000 | 894 | 2000 |
Constrained clustering: Advances in algorithms, theory, and applications S Basu, I Davidson, K Wagstaff Chapman and Hall/CRC, 2008 | 751 | 2008 |
Machine learning that matters K Wagstaff Proceedings of the Twenty-Ninth International Conference on Machine Learning …, 2012 | 400 | 2012 |
Mining GPS traces for map refinement S Schroedl, K Wagstaff, S Rogers, P Langley, C Wilson Data mining and knowledge Discovery 9, 59-87, 2004 | 329 | 2004 |
Noun phrase coreference as clustering C Cardie, K Wagstaff 1999 Joint SIGDAT Conference on Empirical Methods in Natural Language …, 1999 | 322 | 1999 |
Measuring constraint-set utility for partitional clustering algorithms I Davidson, KL Wagstaff, S Basu European conference on principles of data mining and knowledge discovery …, 2006 | 283 | 2006 |
Machine learning for science and society C Rudin, KL Wagstaff Machine Learning 95, 1-9, 2014 | 157 | 2014 |
The commensal real-time ASKAP fast-transients (CRAFT) survey JP Macquart, M Bailes, NDR Bhat, GC Bower, JD Bunton, S Chatterjee, ... Publications of the Astronomical Society of Australia 27 (3), 272-282, 2010 | 153 | 2010 |
Multidocument summarization via information extraction M White, T Korelsky, C Cardie, V Ng, D Pierce, K Wagstaff Proceedings of the first international conference on Human language …, 2001 | 148 | 2001 |
VAST: an ASKAP survey for variables and slow transients T Murphy, S Chatterjee, DL Kaplan, J Banyer, ME Bell, HE Bignall, ... Publications of the Astronomical Society of Australia 30, e006, 2013 | 141 | 2013 |
Intelligent clustering with instance-level constraints KL Wagstaff Cornell University, 2002 | 138 | 2002 |
Clustering with missing values: no imputation required. K Wagstaff Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space …, 2004 | 111 | 2004 |
Alpha seeding for support vector machines D DeCoste, K Wagstaff Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000 | 110 | 2000 |
Onboard autonomy on the intelligent payload experiment cubesat mission S Chien, J Doubleday, DR Thompson, KL Wagstaff, J Bellardo, C Francis, ... Journal of Aerospace Information Systems 14 (6), 307-315, 2017 | 98 | 2017 |
others,“Constrained k-means clustering with background knowledge,” K Wagstaff, C Cardie, S Rogers, S Schrödl Proceedings of the 2001 International Conference on Machine Learning (ICML …, 2001 | 95 | 2001 |
When is constrained clustering beneficial, and why KL Wagstaff, S Basu, I Davidson Ionosphere 58 (60.1), 62-63, 2006 | 92 | 2006 |
Active constrained clustering by examining spectral eigenvectors Q Xu, M desJardins, KL Wagstaff Discovery Science: 8th International Conference, DS 2005, Singapore, October …, 2005 | 81 | 2005 |
V-fastr: The vlba fast radio transients experiment RB Wayth, WF Brisken, AT Deller, WA Majid, DR Thompson, SJ Tingay, ... The Astrophysical Journal 735 (2), 97, 2011 | 72 | 2011 |
Deep mars: Cnn classification of mars imagery for the pds imaging atlas K Wagstaff, Y Lu, A Stanboli, K Grimes, T Gowda, J Padams Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 71 | 2018 |