Gautam Kunapuli

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Sriraam NatarajanUniversity of Texas at DallasVerified email at utdallas.edu
Jude ShavlikProfessor of Computer Science and of Biostatistics & Medical Informatics, University of WisconsinVerified email at cs.wisc.edu
Kristin P. BennettProfessor of Mathematical Sciences, Renssealer Polytechnic InstituteVerified email at rpi.edu
Jong-Shi PangDaniel J. Epstein Chair Professor of Industrial and Systems EngineeringVerified email at usc.edu
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Devendra Singh DhamiJunior Research Group Leader, hessian.AIVerified email at tu-darmstadt.de
David PageDirector, Whitehead InstituteVerified email at wi.mit.edu
Priya GanapathyUtopiaCompression CorporationVerified email at utopiacompression.com
Richard MaclinProfessor of Computer Science, University of Minnesota DuluthVerified email at d.umn.edu
Mayukh DasSenior Research Scientist at Microsoft Research, India | M365 ResearchVerified email at microsoft.com
Prasad TadepalliProfessor of Computer Science, Oregon State UniversityVerified email at eecs.oregonstate.edu
John MitchellProf of Mathematical Sciences, RPIVerified email at rpi.edu
Tushar KhotAllen Institute for AI; University of Wisconsin-MadisonVerified email at cs.wisc.edu
Trevor WalkerGoogleVerified email at usa.net
Siwen YanUniversity of Texas at DallasVerified email at utdallas.edu
Steven CenUniversity of Southern CaliforniaVerified email at usc.edu
Vinay DuddalwarProfessor, Radiology, Urology and Biomedical Engineering University of Southern CaliforniaVerified email at med.usc.edu
Bino VargheseKeck School of MedicineVerified email at med.usc.edu
Bhushan DesaiUniversity of Southern CaliforniaVerified email at usc.edu
Nandini RamananPalo Alto NetworksVerified email at paloaltonetworks.com

Gautam Kunapuli

Motive

Verified email at gomotive.com - Homepage

AI/ML Non-Convex Optimization Human-Allied ML


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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	103	2010
Classification model selection via bilevel programming G Kunapuli, KP Bennett, J Hu, JS Pang Optimization Methods & Software 23 (4), 475-489, 2008	80	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	75	2006
Bilevel optimization and machine learning KP Bennett, G Kunapuli, J Hu, JS Pang Computational Intelligence: Research Frontiers: IEEE World Congress on …, 2008	63	2008
Mirror descent for metric learning: A unified approach G Kunapuli, J Shavlik Machine Learning and Knowledge Discovery in Databases: European Conference …, 2012	51	2012
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	49	2018
Bilevel model selection for support vector machines G Kunapuli, K Bennett, J Hu, JS Pang CRM proceedings and lecture notes 45, 129-158, 2008	46	2008
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	44	2019
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	42	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	34	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	32	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	26	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
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	18	2019
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	16	2021
A bilevel optimization approach to machine learning G Kunapuli Rensselaer Polytechnic Institute, 2008	16	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	14	2020
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
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	10	2018

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