| An ADMM based framework for automl pipeline configuration S Liu, P Ram, D Vijaykeerthy, D Bouneffouf, G Bramble, H Samulowitz, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4892-4899, 2020 | 89 | 2020 |
| AutoAI-TS: AutoAI for time series forecasting SY Shah, D Patel, L Vu, XH Dang, B Chen, P Kirchner, H Samulowitz, ... Proceedings of the 2021 International Conference on Management of Data, 2584 …, 2021 | 48 | 2021 |
| Automated data science for relational data HT Lam, B Buesser, H Min, TN Minh, M Wistuba, U Khurana, G Bramble, ... 2021 IEEE 37th International Conference on Data Engineering (ICDE), 2689-2692, 2021 | 16 | 2021 |
| Automated artificial intelligence radial visualization T Salonidis, J Eversman, D Wang, A Swain, G Bramble, L Ju, N Mazzitelli, ... US Patent 11,514,361, 2022 | 12 | 2022 |
| Automated machine learning pipeline generation B Chen, L Vu, SY Shah, XH Dang, PD Kirchner, SE Han, JH Yang, ... US Patent 11,620,582, 2023 | 9 | 2023 |
| Automated machine learning via ADMM S Liu, P Ram, D Bouneffouf, G Bramble, AR Conn, H Samulowitz, ... CoRR, 2019 | 8 | 2019 |
| Neurology-as-a-Service for the Developing World T Dharamsi, P Das, T Pedapati, G Bramble, V Muthusamy, H Samulowitz, ... arXiv preprint arXiv:1711.06195, 2017 | 7 | 2017 |
| Automated model pipeline generation with entity monitoring, interaction, and intervention D Wang, A Chaudhary, JH Yang, B Chen, G Bramble, C Gan, U Kartoun, ... US Patent App. 16/994,923, 2022 | 5 | 2022 |
| Solving constrained cash problems with admm P Ram, S Liu, D Vijaykeerthi, D Wang, D Bouneffouf, G Bramble, ... arXiv preprint arXiv:2006.09635, 2020 | 5 | 2020 |
| Automated machine learning using nearest neighbor recommender systems S Sathe, G Bramble, HC Samulowitz, CC Aggarwal US Patent 11,941,541, 2024 | 2 | 2024 |
| Methods for automatically configuring performance evaluation schemes for machine learning algorithms B Zhang, G Bramble, P Ram, HC Samulowitz US Patent 11,681,931, 2023 | 2 | 2023 |
| Automated data quality inspection and improvement for automated machine learning A Chaudhary, D Wang, A Valente, CM Spina, H Patel, N Gupta, ... US Patent App. 17/104,642, 2022 | 2 | 2022 |
| Using meta-learning to optimize automatic selection of machine learning pipelines D Wang, C Gan, G Bramble, L Amini, HC Samulowitz, KA Kate, B Chen, ... US Patent App. 16/990,965, 2022 | 2 | 2022 |
| Automated time series forecasting pipeline generation L Vu, B Chen, XH Dang, PD Kirchner, SY Shah, DC Patel, SE Han, ... US Patent 11,966,340, 2024 | 1 | 2024 |
| Distributed resource-aware training of machine learning pipelines S Sathe, G Bramble, L Vu, T Salonidis US Patent 11,829,799, 2023 | 1 | 2023 |
| Toward Theoretical Guidance for Two Common Questions in Practical Cross-Validation based Hyperparameter Selection P Ram, AG Gray, HC Samulowitz, G Bramble Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 1 | 2023 |
| Automated time series forecasting pipeline ranking B Chen, L Vu, DC Patel, SY Shah, G Bramble, PD Kirchner, ... US Patent App. 17/452,287, 2022 | 1 | 2022 |
| Unsupervised feature learning for relational data TL Hoang, L Vu, T Salonidis, G Bramble US Patent 11,416,469, 2022 | 1 | 2022 |
| Automated analysis generation for machine learning system A Chaudhary, D Wang, DJ Piorkowski, DM Gruen, C Gan, PD Kirchner, ... US Patent App. 17/020,299, 2022 | 1 | 2022 |
| Machine learning with multiple constraints P Ram, D Wang, D Vijaykeerthy, V Saxena, S Liu, A Chaudhary, ... US Patent App. 17/015,243, 2022 | 1 | 2022 |
