| Automated bug assignment: Ensemble-based machine learning in large scale industrial contexts L Jonsson, M Borg, D Broman, K Sandahl, S Eldh, P Runeson Empirical Software Engineering 21 (4), 1533-1578, 2016 | 178 | 2016 |
| Towards automated anomaly report assignment in large complex systems using stacked generalization L Jonsson, D Broman, K Sandahl, S Eldh 2012 IEEE Fifth International Conference on Software Testing, Verification …, 2012 | 28 | 2012 |
| Polya Urn Latent Dirichlet Allocation: a doubly sparse massively parallel sampler A Terenin, M Magnusson, L Jonsson, D Draper IEEE transactions on pattern analysis and machine intelligence 41 (7), 1709-1719, 2018 | 22 | 2018 |
| Automatic Localization of Bugs to Faulty Components in Large Scale Software Systems using Bayesian Classification L Jonsson, D Broman, M Magnusson, K Sandahl, M Villani, S Eldh 2016 IEEE International Conference on Software Quality, Reliability and …, 2016 | 17 | 2016 |
| DOLDA: a regularized supervised topic model for high-dimensional multi-class regression M Magnusson, L Jonsson, M Villani Computational Statistics 35 (1), 175-201, 2020 | 16 | 2020 |
| Increasing anomaly handling efficiency in large organizations using applied machine learning L Jonsson 2013 35th International Conference on Software Engineering (ICSE), 1361-1364, 2013 | 14 | 2013 |
| Machine Learning-Based Bug Handling in Large-Scale Software Development L Jonsson Linköping University Electronic Press, 2018 | 13 | 2018 |
| Sparse partially collapsed mcmc for parallel inference in topic models M Magnusson, L Jonsson, M Villani, D Broman Journal of Computational and Graphical Statistics 27 (2), 449-463, 2018 | 10 | 2018 |
| Sparse partially collapsed mcmc for parallel inference in topic models M Magnusson, L Jonsson, M Villani, D Broman arXiv preprint arXiv:1506.03784, 2015 | 8 | 2015 |
| Parallelizing LDA using partially collapsed Gibbs sampling M Magnusson, L Jonsson, M Villani, D Broman ArXiv e-prints, 2015 | 7 | 2015 |
| BERTicsson: A Recommender System For Troubleshooting NMI Grimalt, S Shalmashi, F Yaghoubi, L Jonsson, AH Payberah | 4 | 2022 |
| The Cambridge Law Corpus: A Dataset for Legal AI Research A Östling, H Sargeant, H Xie, LK Bull, A Terenin, L Jonsson, ... Thirty-seventh Conference on Neural Information Processing Systems Datasets …, 2023 | 3 | 2023 |
| The Cambridge Law Corpus: A Corpus for Legal AI Research A Östling, H Sargeant, H Xie, L Bull, A Terenin, L Jonsson, M Magnusson, ... Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Adopting Automated Bug Assignment in Practice: A Longitudinal Case Study at Ericsson M Borg, L Jonsson, E Engström, B Bartalos, A Szabó arXiv preprint arXiv:2209.08955, 2022 | 1 | 2022 |
| Adopting Automated Bug Assignment in Practice--A Registered Report of an Industrial Case Study M Borg, L Jonsson, E Engström, B Bartalos, A Szabo arXiv preprint arXiv:2109.13635, 2021 | 1 | 2021 |
| Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models A Terenin, M Magnusson, L Jonsson arXiv preprint arXiv:1906.02416, 2019 | 1 | 2019 |
| DOLDA M Magnusson, L Jonsson, M Villani Springer Verlag, 2020 | | 2020 |
| Sparse Parallel Training for Hierarchical Dirichlet Process Topic Models A Terenin, M Magnusson, L Jonsson Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | | 2020 |
| Pólya Urn Latent Dirichlet Allocation A Terenin, M Magnusson, L Jonsson, D Draper | | 2018 |
| The More the Merrier: Leveraging on the Bug Inflow to Guide Software Maintenance M Borg, L Jonsson Tiny Transactions on Computer Science 3, 2015 | | 2015 |
David BromanProfessor, KTH Royal Institute of Technology在 kth.se 的电子邮件经过验证
