| 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 | 116 | 2015 |
| 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 | 91 | 2014 |
| The power of system call traces: Predicting the software energy consumption impact of changes K Aggarwal, Z Chenlei, J Campbell, A Hindle, E Stroulia | 82 | 2014 |
| 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 | 64 | 2019 |
| 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 | 60 | 2015 |
| Benchmarking regression methods: A comparison with CGAN K Aggarwal, M Kirchmeyer, P Yadav, SS Keerthi, P Gallinari arXiv preprint arXiv:1905.12868, 2019 | 58* | 2019 |
| Using machine translation for converting python 2 to python 3 code K Aggarwal, M Salameh, A Hindle PeerJ PrePrints, 2015 | 53 | 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 | 49 | 2018 |
| 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 | 26 | 2018 |
| Efficient continual pre-training for building domain specific large language models Y Xie, K Aggarwal, A Ahmad Findings of the Association for Computational Linguistics ACL 2024, 10184–10201, 2024 | 24 | 2024 |
| 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 | 24 | 2019 |
| 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 | 18 | 2015 |
| 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 | 12 | 2019 |
| Multi task learning with incomplete labels for predictive maintenance C Zhang, AK Farahat, C Gupta, K Aggarwal US Patent 11,231,703, 2022 | 6 | 2022 |
| 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 | 6 | 2020 |
| Data Mining Techniques for Social Networks Analysis. K Aggarwal, K Kapoor, J Srivastava Encyclopedia of Social Network Analysis and Mining. 2nd Ed., 2018 | 6 | 2018 |
| Unified framework for dynamic clustering and discrete time event prediction K Aggarwal, G Theocharous, A Rao US Patent App. 16/933,361, 2022 | 3 | 2022 |
| Using clinical notes for icu management K Aggarwal, S Khadanga, SR Joty, J Srivastava US Patent App. 17/330,908, 2021 | 3 | 2021 |
| 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 |
| ECG-QALM: Entity-controlled synthetic text generation using contextual Q&A for NER K Aggarwal, H Jin, A Ahmad Findings of the Association for Computational Linguistics: ACL 2023, 5649–5660, 2023 | 2 | 2023 |
Abram HindleUniversity of AlbertaVerified email at ualberta.ca
