| Detecting duplicate bug reports with software engineering domain knowledge K Aggarwal, F Timbers, T Rutgers, A Hindle, E Stroulia, R Greiner Journal of Software: Evolution and Process 29 (3), e1821, 2017 | 69 | 2017 |
| Detecting duplicate bug reports with software engineering domain knowledge K Aggarwal, T Rutgers, F Timbers, A Hindle, R Greiner, E Stroulia IEEE 22nd International Conference on Software Analysis, Evolution and …, 2015 | 69 | 2015 |
| The power of system call traces: predicting the software energy consumption impact of changes. K Aggarwal, C Zhang, JC Campbell, A Hindle, E Stroulia CASCON 14, 219-233, 2014 | 60 | 2014 |
| Co-evolution of project documentation and popularity within GitHub K Aggarwal, A Hindle, E Stroulia Proceedings of the 11th Working Conference on Mining Software Repositories …, 2014 | 58 | 2014 |
| Greenadvisor: A tool for analyzing the impact of software evolution on energy consumption K Aggarwal, A Hindle, E Stroulia 2015 IEEE international conference on software maintenance and evolution …, 2015 | 40 | 2015 |
| Two birds with one network: Unifying failure event prediction and time-to-failure modeling K Aggarwal, O Atan, AK Farahat, C Zhang, K Ristovski, C Gupta 2018 IEEE International Conference on Big Data (Big Data), 1308-1317, 2018 | 22 | 2018 |
| A system-call based model of software energy consumption without hardware instrumentation SA Chowdhury, LN Kumar, MT Imam, MSM Jabbar, V Sapra, K Aggarwal, ... 2015 Sixth International Green and Sustainable Computing Conference (IGSC), 1-6, 2015 | 14 | 2015 |
| Using Clinical Notes with Time Series Data for ICU Management S Khadanga, K Aggarwal, S Joty, J Srivastava Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 12 | 2019 |
| A Structured Learning Approach with Neural Conditional Random Fields for Sleep Staging K Aggarwal, S Khadanga, S Joty, L Kazaglis, J Srivastava 2018 IEEE International Conference on Big Data (Big Data), 1318-1327, 2018 | 12* | 2018 |
| Using machine translation for converting Python 2 to Python 3 code K Aggarwal, M Salameh, A Hindle PeerJ PrePrints, 2015 | 10 | 2015 |
| Benchmarking regression methods: a comparison with CGAN K Aggarwal, M Kirchmeyer, P Yadav, SS Keerthi, P Gallinari arXiv preprint arXiv:1905.12868, 2019 | 9* | 2019 |
| Adversarial Unsupervised Representation Learning for Activity Time-Series K Aggarwal, S Joty, L Fernandez-Luque, J Srivastava Proceedings of the AAAI Conference on Artificial Intelligence 33, 834-841, 2019 | 8 | 2019 |
| Domain Adaptation in Display Advertising: An Application for Partner Cold-Start K Aggarwal, P Yadav, KS Selvaraj Proceedings of the 13th ACM Conference on Recommender Systems, 178-186, 2019 | 4 | 2019 |
| Data Mining Techniques for Social Networks Analysis. K Aggarwal, K Kapoor, J Srivastava Encyclopedia of Social Network Analysis and Mining. 2nd Ed., 2018 | 4 | 2018 |
| Co-morbidity exploration on wearables activity data using unsupervised pre-training and multi-task learning K Aggarwal, S Joty, LF Luque, J Srivastava arXiv preprint arXiv:1712.09527, 2017 | 3 | 2017 |
| Combining text and image data for product recommendability modeling M Capelo, K Aggarwal, P Yadav 2019 IEEE International Conference on Big Data (Big Data), 5992-5994, 2019 | 2 | 2019 |
| Multi task learning with incomplete labels for predictive maintenance C Zhang, AK Farahat, C Gupta, K Aggarwal US Patent App. 16/540,810, 2021 | | 2021 |
| Computer architecture for identifying sleep stages K Aggarwal, S Khadanga, SR Joty, L Kazaglis, J Srivastava US Patent App. 16/932,348, 2021 | | 2021 |
| Dynamic Clustering with Discrete Time Event Prediction K Aggarwal, G Theocharous, AB Rao Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | | 2020 |
| Temporal Proximity Filtering A Kumar, K Aggarwal, P Schrater Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing …, 2019 | | 2019 |
Abram HindleUniversity of AlbertaVerified email at ualberta.ca
