| Guiding combinatorial optimization with uct A Sabharwal, H Samulowitz, C Reddy International conference on integration of artificial intelligence (AI) and …, 2012 | 92 | 2012 |
| Learning goal-decomposition rules using exercises C Reddy, P Tadepalli ICML, 278-286, 1997 | 72 | 1997 |
| The slab-design problem in the steel industry M Dawande, J Kalagnanam, HS Lee, C Reddy, S Siegel, M Trumbo Interfaces 34 (3), 215-225, 2004 | 66 | 2004 |
| Learning first-order acyclic Horn programs from entailment C Reddy, P Tadepalli International Conference on Inductive Logic Programming, 23-37, 1998 | 53 | 1998 |
| Finishing line scheduling in the steel industry H Okano, AJ Davenport, M Trumbo, C Reddy, K Yoda, M Amano IBM Journal of research and development 48 (5.6), 811-830, 2004 | 40 | 2004 |
| Learning Horn definitions: Theory and an application to planning C Reddy, P Tadepalli New Generation Computing 17 (1), 77-98, 1999 | 35 | 1999 |
| Production design for plate products in the steel industry S Dash, J Kalagnanam, C Reddy, SH Song IBM journal of research and development 51 (3.4), 345-362, 2007 | 32 | 2007 |
| How to foster innovation: A data-driven approach to measuring economic competitiveness C Kuhlman, KN Ramamurthy, P Sattigeri, AC Lozano, L Cao, C Reddy, ... IBM Journal of Research and Development 61 (6), 11: 1-11: 12, 2017 | 31 | 2017 |
| Learning Horn definitions with equivalence and membership queries C Reddy, P Tadepalli International Conference on Inductive Logic Programming, 243-255, 1997 | 25 | 1997 |
| Snappy: A simple algorithm portfolio H Samulowitz, C Reddy, A Sabharwal, M Sellmann International Conference on Theory and Applications of Satisfiability …, 2013 | 22 | 2013 |
| Towards cognitive automation of data science A Biem, M Butrico, M Feblowitz, T Klinger, Y Malitsky, K Ng, A Perer, ... Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015 | 20 | 2015 |
| Modeling and simulation of building energy performance for portfolios of public buildings YM Lee, F Liu, L An, H Jiang, C Reddy, R Horesh, P Nevill, E Meliksetian, ... Proceedings of the 2011 winter simulation conference (WSC), 915-927, 2011 | 20 | 2011 |
| Theory-guided empirical speedup learning of goal decomposition rules C Reddy, P Tadepalli, S Roncagliolo ICML, 1996 | 16 | 1996 |
| Interpretable Clustering via Multi-Polytope Machines C Lawless, J Kalagnanam, LM Nguyen, D Phan, C Reddy Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7309-7316, 2022 | 9 | 2022 |
| Smart-ML: A System for Machine Learning Model Exploration using Pipeline Graph D Patel, S Shrivastava, W Gifford, S Siegel, J Kalagnanam, C Reddy 2020 IEEE International Conference on Big Data (Big Data), 1604-1613, 2020 | 8 | 2020 |
| An application of constraint programming to generating detailed operations schedules for steel manufacturing A Davenport, J Kalagnanam, C Reddy, S Siegel, J Hou International Conference on Principles and Practice of Constraint …, 2007 | 8 | 2007 |
| The slab design problem in the steel industry M Dawande, J Kalagnanam, HS Lee, C Reddy, S Siegel, M Trumbo Handbook of Production Scheduling, 243-264, 2006 | 4 | 2006 |
| Inductive logic programming for speedup learning C Reddy, P Tadepalli Proceedings of the IJCAL97 workshop on Frontiers of Inductive Logic …, 1997 | 4 | 1997 |
| Providing Cooperative Data Analytics for Real Applications Using Machine Learning A Iyengar, J Kalagnanam, D Patel, C Reddy, S Shrivastava 2019 IEEE 39th International Conference on Distributed Computing Systems …, 2019 | 2 | 2019 |
| Asset Modeling using Serverless Computing S Jayaraman, C Reddy, E Khabiri, D Patel, A Bhamidipaty, J Kalagnanam 2021 IEEE International Conference on Big Data (Big Data), 4084-4090, 2021 | 1 | 2021 |
