On the global solution of linear programs with linear complementarity constraints J Hu, JE Mitchell, JS Pang, KP Bennett, G Kunapuli SIAM Journal on Optimization 19 (1), 445-471, 2008 | 138 | 2008 |
Multi-agent inverse reinforcement learning S Natarajan, G Kunapuli, K Judah, P Tadepalli, K Kersting, J Shavlik 2010 ninth international conference on machine learning and applications …, 2010 | 120 | 2010 |
Classification model selection via bilevel programming G Kunapuli, KP Bennett, J Hu, JS Pang Optimization Methods & Software 23 (4), 475-489, 2008 | 99 | 2008 |
Model selection via bilevel optimization KP Bennett, J Hu, X Ji, G Kunapuli, JS Pang The 2006 IEEE International Joint Conference on Neural Network Proceedings …, 2006 | 92 | 2006 |
Bilevel optimization and machine learning KP Bennett, G Kunapuli, J Hu, JS Pang IEEE world congress on computational intelligence, 25-47, 2008 | 89 | 2008 |
Bilevel model selection for support vector machines G Kunapuli, K Bennett, J Hu, JS Pang CRM proceedings and lecture notes 45, 129-158, 2008 | 59 | 2008 |
A decision-support tool for renal mass classification G Kunapuli, BA Varghese, P Ganapathy, B Desai, S Cen, M Aron, I Gill, ... Journal of Digital Imaging 31, 929-939, 2018 | 58 | 2018 |
Classification of burn injury using Raman spectroscopy and optical coherence tomography: An ex-vivo study on porcine skin LP Rangaraju, G Kunapuli, D Every, OD Ayala, P Ganapathy, ... Burns 45 (3), 659-670, 2019 | 52 | 2019 |
Mirror descent for metric learning: A unified approach G Kunapuli, J Shavlik Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012 | 52 | 2012 |
Guiding autonomous agents to better behaviors through human advice G Kunapuli, P Odom, JW Shavlik, S Natarajan 2013 IEEE 13th international conference on data mining, 409-418, 2013 | 47 | 2013 |
Online knowledge-based support vector machines G Kunapuli, KP Bennett, A Shabbeer, R Maclin, J Shavlik Machine Learning and Knowledge Discovery in Databases: European Conference …, 2010 | 37 | 2010 |
Learning from imbalanced data in relational domains: A soft margin approach S Yang, T Khot, K Kersting, G Kunapuli, K Hauser, S Natarajan 2014 IEEE International Conference on Data Mining, 1085-1090, 2014 | 36 | 2014 |
Drug‐drug interaction discovery: kernel learning from heterogeneous similarities DS Dhami, G Kunapuli, M Das, D Page, S Natarajan Smart Health 9, 88-100, 2018 | 29 | 2018 |
Relational restricted boltzmann machines: A probabilistic logic learning approach N Kaur, G Kunapuli, T Khot, K Kersting, W Cohen, S Natarajan Inductive Logic Programming: 27th International Conference, ILP 2017 …, 2018 | 20 | 2018 |
Structure learning for relational logistic regression: an ensemble approach N Ramanan, G Kunapuli, T Khot, B Fatemi, SM Kazemi, D Poole, ... Data Mining and Knowledge Discovery 35, 2089-2111, 2021 | 19 | 2021 |
Fast relational probabilistic inference and learning: Approximate counting via hypergraphs M Das, DS Dhami, G Kunapuli, K Kersting, S Natarajan Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7816-7824, 2019 | 19 | 2019 |
A bilevel optimization approach to machine learning G Kunapuli Rensselaer Polytechnic Institute, 2008 | 19 | 2008 |
Neural networks for relational data N Kaur, G Kunapuli, S Joshi, K Kersting, S Natarajan Inductive Logic Programming: 29th International Conference, ILP 2019 …, 2020 | 18 | 2020 |
On Whom Should I Perform this Lab Test Next? An Active Feature Elicitation Approach. S Natarajan, S Das, N Ramanan, G Kunapuli, P Radivojac IJCAI, 3498-3505, 2018 | 14 | 2018 |
Automating the ILP setup task: Converting user advice about specific examples into general background knowledge T Walker, C O’Reilly, G Kunapuli, S Natarajan, R Maclin, D Page, ... Inductive Logic Programming: 20th International Conference, ILP 2010 …, 2011 | 11 | 2011 |