Karan Aggarwal
Karan Aggarwal
Graduate Student, University of Minnesota
Verified email at
Cited by
Cited by
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
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
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
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
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
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
Benchmarking regression methods: A comparison with CGAN
K Aggarwal, M Kirchmeyer, P Yadav, SS Keerthi, P Gallinari
arXiv preprint arXiv:1905.12868, 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
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
Using machine translation for converting python 2 to python 3 code
K Aggarwal, M Salameh, A Hindle
PeerJ PrePrints, 2015
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
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
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
Data mining techniques for social networks analysis
K Aggarwal, K Kapoor, J Srivastava
Journal: Encyclopedia of Social Network Analysis and Mining, 1-11, 2017
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
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
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
Multi task learning with incomplete labels for predictive maintenance
C Zhang, AK Farahat, C Gupta, K Aggarwal
US Patent 11,231,703, 2022
Unified framework for dynamic clustering and discrete time event prediction
K Aggarwal, G Theocharous, A Rao
US Patent App. 16/933,361, 2022
Using clinical notes for icu management
K Aggarwal, S Khadanga, SR Joty, J Srivastava
US Patent App. 17/330,908, 2021
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