| Feature selection for unsupervised learning JG Dy, CE Brodley Journal of machine learning research 5 (Aug), 845-889, 2004 | 1429 | 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 | 754 | 2009 |
| Learning to prompt for continual learning Z Wang, Z Zhang, CY Lee, H Zhang, R Sun, X Ren, G Su, V Perot, J Dy, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 646 | 2022 |
| 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 | 554 | 2018 |
| 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 | 462 | 2008 |
| 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 | 453 | 2018 |
| Active learning from crowds Y Yan, GM Fung, R Rosales, JG Dy Proceedings of the 28th international conference on machine learning (ICML …, 2011 | 425 | 2011 |
| Dualprompt: Complementary prompting for rehearsal-free continual learning Z Wang, Z Zhang, S Ebrahimi, R Sun, H Zhang, CY Lee, X Ren, G Su, ... European Conference on Computer Vision, 631-648, 2022 | 390 | 2022 |
| Feature subset selection and order identification for unsupervised learning JG Dy, CE Brodley Icml, 247-254, 2000 | 381 | 2000 |
| 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 | 325 | 2003 |
| Cluster: An unsupervised algorithm for modeling Gaussian mixtures CA Bouman, M Shapiro, GW Cook, CB Atkins, H Cheng | 319 | 1997 |
| Genetic landscape of chronic obstructive pulmonary disease identifies heterogeneous cell-type and phenotype associations P Sakornsakolpat, D Prokopenko, M Lamontagne, NF Reeve, AL Guyatt, ... Nature genetics 51 (3), 494-505, 2019 | 314 | 2019 |
| 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 | 288 | 2005 |
| Exposing the fingerprint: Dissecting the impact of the wireless channel on radio fingerprinting A Al-Shawabka, F Restuccia, S D’Oro, T Jian, BC Rendon, N Soltani, J Dy, ... IEEE INFOCOM 2020-IEEE Conference on Computer Communications, 646-655, 2020 | 255 | 2020 |
| 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 | 255 | 2010 |
| 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 | 224 | 2003 |
| Learning from multiple annotators with varying expertise Y Yan, R Rosales, G Fung, R Subramanian, J Dy Machine learning 95, 291-327, 2014 | 220 | 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 | 219 | 2014 |
| 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 | 218 | 2010 |
| COPDGene® 2019: redefining the diagnosis of chronic obstructive pulmonary disease KE Lowe, EA Regan, A Anzueto, E Austin, JHM Austin, TH Beaty, ... Chronic Obstructive Pulmonary Diseases: Journal of the COPD Foundation 6 (5 …, 2019 | 214 | 2019 |
