| An empirical study of api stability and adoption in the android ecosystem T McDonnell, B Ray, M Kim 2013 IEEE International Conference on Software Maintenance, 70-79, 2013 | 387 | 2013 |
| Neural information retrieval: At the end of the early years KD Onal, Y Zhang, IS Altingovde, MM Rahman, P Karagoz, A Braylan, ... Information Retrieval Journal 21, 111-182, 2018 | 159 | 2018 |
| Why is that relevant? collecting annotator rationales for relevance judgments T McDonnell, M Lease, M Kutlu, T Elsayed Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 4 …, 2016 | 122 | 2016 |
| Neural information retrieval: A literature review Y Zhang, MM Rahman, A Braylan, B Dang, HL Chang, H Kim, ... arXiv preprint arXiv:1611.06792, 2016 | 65 | 2016 |
| Annotator rationales for labeling tasks in crowdsourcing M Kutlu, T McDonnell, T Elsayed, M Lease Journal of Artificial Intelligence Research 69, 143-189, 2020 | 37 | 2020 |
| Your behavior signals your reliability: Modeling crowd behavioral traces to ensure quality relevance annotations T Goyal, T McDonnell, M Kutlu, T Elsayed, M Lease Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 6 …, 2018 | 30 | 2018 |
| Crowd vs. expert: What can relevance judgment rationales teach us about assessor disagreement? M Kutlu, T McDonnell, Y Barkallah, T Elsayed, M Lease The 41st International ACM SIGIR Conference on Research & Development in …, 2018 | 27 | 2018 |
| Divide and conquer: neuroevolution for multiclass classification T McDonnell, S Andoni, E Bonab, S Cheng, JH Choi, J Goode, K Moore, ... Proceedings of the genetic and evolutionary computation conference, 474-481, 2018 | 22 | 2018 |
| Ensembling of neural network models S Andoni, KD Moore, EM Bonab, J Choi, TS McDonnell US Patent 10,635,978, 2020 | 21 | 2020 |
| Automated model building search space reduction TS McDonnell, S Andoni, J Choi, J Goode, Y Lan, KD Moore, G Sellers US Patent 10,657,447, 2020 | 16 | 2020 |
| An Thanh Nguyen, Dan Xu, Byron C Y Zhang, MM Rahman, A Braylan, B Dang, HL Chang, H Kim, ... Wallace, and Matthew Lease, 2016 | 11 | 2016 |
| The many benefits of annotator rationales for relevance judgments T McDonnell, M Kutlu, T Elsayed, M Lease International Joint Conferences on Artificial Intelligence, 2017 | 10 | 2017 |
| Automated neural network generation using fitness estimation TS McDonnell, B Greenwood US Patent 10,685,286, 2020 | 7 | 2020 |
| Surrogate-assisted neuroevolution B Greenwood, T McDonnell Proceedings of the Genetic and Evolutionary Computation Conference, 1048-1056, 2022 | 6 | 2022 |
| Mix and match: collaborative expert-crowd judging for building test collections accurately and affordably M Kutlu, T McDonnell, A Sheshadri, T Elsayed, M Lease arXiv preprint arXiv:1806.00755, 2018 | 6 | 2018 |
| Cooperative use of a genetic algorithm and an optimization trainer for autoencoder generation S Andoni, U Yadav, TS McDonnell US Patent 10,733,512, 2020 | 5 | 2020 |
| Anomaly detection using a dimensional-reduction model S Andoni, U Yadav, TS McDonnell US Patent 11,443,194, 2022 | 2 | 2022 |
| Matrix representation of neural networks TS McDonnell, B Greenwood US Patent App. 17/129,023, 2021 | 2 | 2021 |
| Anomaly detection using a non-mirrored dimensional-reduction model S Andoni, U Yadav, TS McDonnell US Patent 12,014,279, 2024 | 1 | 2024 |
| Diverse clustering of a data set J Choi, T McDONNELL, Y Lan, KD Moore, CY Ho US Patent App. 17/500,343, 2023 | 1 | 2023 |
Matt LeaseProfessor, School of Information, University of Texas at AustinVerified email at utexas.edu
