| Feature selection for unsupervised learning JG Dy, CE Brodley Journal of machine learning research 5 (Aug), 845-889, 2004 | 1096 | 2004 |
| Feature selection for unsupervised learning JG Dy, CE Brodley Journal of machine learning research 5 (Aug), 845-889, 2004 | 1096 | 2004 |
| Monitoring motor fluctuations in patients with Parkinson's disease using wearable sensors S Patel, K Lorincz, R Hughes, N Huggins, J Growdon, D Standaert, ... IEEE transactions on information technology in biomedicine 13 (6), 864-873, 2009 | 577 | 2009 |
| Active learning from crowds Y Yan, R Rosales, G Fung, JG Dy ICML, 2011 | 341 | 2011 |
| Feature subset selection and order identification for unsupervised learning JG Dy, CE Brodley ICML, 247-254, 2000 | 341 | 2000 |
| Impact of imputation of missing values on classification error for discrete data A Farhangfar, L Kurgan, J Dy Pattern Recognition 41 (12), 3692-3705, 2008 | 327 | 2008 |
| Unsupervised feature selection applied to content-based retrieval of lung images JG Dy, CE Brodley, A Kak, LS Broderick, AM Aisen IEEE transactions on pattern analysis and machine intelligence 25 (3), 373-378, 2003 | 293 | 2003 |
| Cluster: An unsupervised algorithm for modeling Gaussian mixtures CA Bouman, M Shapiro, GW Cook, CB Atkins, H Cheng | 276 | 1997 |
| Evolving feature selection H Liu, ER Dougherty, JG Dy, K Torkkola, E Tuv, H Peng, C Ding, F Long, ... IEEE Intelligent systems 20 (6), 64-76, 2005 | 234 | 2005 |
| Automated storage and retrieval of thin-section CT images to assist diagnosis: system description and preliminary assessment AM Aisen, LS Broderick, H Winer-Muram, CE Brodley, AC Kak, ... Radiology 228 (1), 265-270, 2003 | 214 | 2003 |
| Modeling annotator expertise: Learning when everybody knows a bit of something Y Yan, R Rosales, G Fung, M Schmidt, G Hermosillo, L Bogoni, L Moy, ... Proceedings of the Thirteenth International Conference on Artificial …, 2010 | 211 | 2010 |
| A hierarchical method for multi-class support vector machines V Vural, JG Dy Proceedings of the twenty-first international conference on Machine learning …, 2004 | 181 | 2004 |
| A novel approach to monitor rehabilitation outcomes in stroke survivors using wearable technology S Patel, R Hughes, T Hester, J Stein, M Akay, JG Dy, P Bonato Proceedings of the IEEE 98 (3), 450-461, 2010 | 178 | 2010 |
| Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks JM Brown, JP Campbell, A Beers, K Chang, S Ostmo, RVP Chan, J Dy, ... JAMA ophthalmology 136 (7), 803-810, 2018 | 167 | 2018 |
| Non-redundant multi-view clustering via orthogonalization Y Cui, XZ Fern, JG Dy Seventh IEEE International Conference on Data Mining (ICDM 2007), 133-142, 2007 | 160 | 2007 |
| Emotion fingerprints or emotion populations? A meta-analytic investigation of autonomic features of emotion categories. EH Siegel, MK Sands, W Van den Noortgate, P Condon, Y Chang, J Dy, ... Psychological bulletin 144 (4), 343, 2018 | 150 | 2018 |
| Multiple non-redundant spectral clustering views D Niu, JG Dy, MI Jordan ICML, 2010 | 139 | 2010 |
| VMM-based intrusion detection system M Moffie, D Kaeli, A Cohen, J Aslam, M Alshawabkeh, J Dy, F Azmandian US Patent 8,719,936, 2014 | 138 | 2014 |
| VMM-based intrusion detection system M Moffie, D Kaeli, A Cohen, J Aslam, M Alshawabkeh, J Dy, F Azmandian US Patent 8,719,936, 2014 | 138 | 2014 |
| Cluster analysis in the COPDGene study identifies subtypes of smokers with distinct patterns of airway disease and emphysema PJ Castaldi, J Dy, J Ross, Y Chang, GR Washko, D Curran-Everett, ... Thorax 69 (5), 416-423, 2014 | 138 | 2014 |
