| Human-AI collaboration in data science: Exploring data scientists' perceptions of automated AI D Wang, JD Weisz, M Muller, P Ram, W Geyer, C Dugan, Y Tausczik, ... Proceedings of the ACM on human-computer interaction 3 (CSCW), 1-24, 2019 | 430 | 2019 |
| MLPACK: A scalable C++ machine learning library RR Curtin, JR Cline, NP Slagle, WB March, P Ram, NA Mehta, AG Gray The Journal of Machine Learning Research 14 (1), 801-805, 2013 | 221 | 2013 |
| Maximum inner-product search using cone trees P Ram, AG Gray Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 207 | 2012 |
| Configurable Machine Learning Method Selection and Parameter Optimization System and Method M Gibiansky, R Riegel, Y Yang, P Ram, A Gray US Patent App. 14/883,522, 2016 | 167 | 2016 |
| Revisiting kd-tree for nearest neighbor search P Ram, K Sinha Proceedings of the 25th acm sigkdd international conference on knowledge …, 2019 | 143 | 2019 |
| Density estimation trees P Ram, AG Gray Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 141 | 2011 |
| Fast Euclidean minimum spanning tree: algorithm, analysis, and applications WB March, P Ram, AG Gray Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 136 | 2010 |
| Efficient retrieval of recommendations in a matrix factorization framework N Koenigstein, P Ram, Y Shavitt Proceedings of the 21st ACM international conference on Information and …, 2012 | 110 | 2012 |
| Model sparsity can simplify machine unlearning J Jia, J Liu, P Ram, Y Yao, G Liu, Y Liu, P Sharma, S Liu Advances in Neural Information Processing Systems 36, 51584-51605, 2023 | 100* | 2023 |
| 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 | 91 | 2020 |
| Linear-time algorithms for pairwise statistical problems P Ram, D Lee, W March, A Gray Advances in Neural Information Processing Systems 22, 2009 | 90 | 2009 |
| Advancing model pruning via bi-level optimization Y Zhang, Y Yao, P Ram, P Zhao, T Chen, M Hong, Y Wang, S Liu Advances in Neural Information Processing Systems 35, 18309-18326, 2022 | 68 | 2022 |
| Fast exact max-kernel search RR Curtin, P Ram, AG Gray Proceedings of the 2013 SIAM International Conference on Data Mining, 1-9, 2013 | 59 | 2013 |
| Tree-independent dual-tree algorithms R Curtin, W March, P Ram, D Anderson, A Gray, C Isbell International Conference on Machine Learning, 1435-1443, 2013 | 47 | 2013 |
| Autoai: Automating the end-to-end ai lifecycle with humans-in-the-loop D Wang, P Ram, DKI Weidele, S Liu, M Muller, JD Weisz, A Valente, ... Companion Proceedings of the 25th International Conference on Intelligent …, 2020 | 45 | 2020 |
| Which space partitioning tree to use for search? P Ram, A Gray Advances in Neural Information Processing Systems 26, 2013 | 38 | 2013 |
| Dual‐tree fast exact max‐kernel search RR Curtin, P Ram Statistical Analysis and Data Mining: The ASA Data Science Journal 7 (4 …, 2014 | 33 | 2014 |
| Rank-approximate nearest neighbor search: Retaining meaning and speed in high dimensions P Ram, D Lee, H Ouyang, A Gray Advances in Neural Information Processing Systems 22, 2009 | 33 | 2009 |
| Exploring context-free languages via planning: The case for automating machine learning M Katz, P Ram, S Sohrabi, O Udrea Proceedings of the International Conference on Automated Planning and …, 2020 | 29 | 2020 |
| Pipeline combinators for gradual automl G Baudart, M Hirzel, K Kate, P Ram, A Shinnar, J Tsay Advances in Neural Information Processing Systems 34, 19705-19718, 2021 | 28 | 2021 |
Alexander GrayCentaur AI InstituteEmail yang diverifikasi di cc.gatech.edu