| MLPACK: A scalable C++ machine learning library RR Curtin, JR Cline, NP Slagle, WB March, P Ram, NA Mehta, AG Gray Journal of Machine Learning Research 14 (Mar), 801-805, 2013 | 176 | 2013 |
| Maximum inner-product search using cone trees P Ram, AG Gray Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 139 | 2012 |
| 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 | 87 | 2010 |
| Density estimation trees P Ram, AG Gray Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 86 | 2011 |
| Linear-time algorithms for pairwise statistical problems P Ram, D Lee, W March, A Gray Advances in Neural Information Processing Systems 22, 1527-1535, 2009 | 75 | 2009 |
| 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 | 71 | 2012 |
| 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 | 47 | 2019 |
| Fast exact max-kernel search RR Curtin, P Ram, AG Gray Proceedings of the 2013 SIAM International Conference on Data Mining, 1-9, 2013 | 41 | 2013 |
| 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 | 33* | 2020 |
| 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 | 32 | 2016 |
| 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 | 32 | 2013 |
| 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, 1536-1544, 2009 | 32 | 2009 |
| Dual‐tree fast exact max‐kernel search RR Curtin, P Ram Statistical Analysis and Data Mining: The ASA Data Science Journal 7 (4 …, 2014 | 26 | 2014 |
| Which space partitioning tree to use for search? P Ram, AG Gray NIPS, 656-664, 2013 | 24 | 2013 |
| Nearest-Neighbor Search on a Time Budget via Max-Margin Trees P Ram, D Lee, AG Gray SIAM Data Mining, 2012 | 19 | 2012 |
| Improved maximum inner product search with better theoretical guarantees O Keivani, K Sinha, P Ram 2017 International Joint Conference on Neural Networks (IJCNN), 2927-2934, 2017 | 10 | 2017 |
| Plug-and-play dual-tree algorithm runtime analysis. RR Curtin, D Lee, WB March, P Ram J. Mach. Learn. Res. 16, 3269-3297, 2015 | 10 | 2015 |
| Revisiting kd-tree for nearest neighbor search P Ram, K Sinha Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 9 | 2019 |
| How can ai automate end-to-end data science? C Aggarwal, D Bouneffouf, H Samulowitz, B Buesser, T Hoang, ... arXiv preprint arXiv:1910.14436, 2019 | 8 | 2019 |
| Improved maximum inner product search with better theoretical guarantee using randomized partition trees O Keivani, K Sinha, P Ram Machine Learning 107 (6), 1069-1094, 2018 | 8 | 2018 |
Alexander GrayIBM Research AIVerified email at cc.gatech.edu
