Vaishnavh Nagarajan

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Zico KolterCarnegie Mellon UniversityVerified email at cs.cmu.edu
Maria-Florina BalcanProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Leandro Soriano MarcolinoLecturer (Assistant Professor), Lancaster UniversityVerified email at lancaster.ac.uk
Milind TambeProfessor & Director CRCS Center @Harvard; Director "AI for Social Good" @Google ResearchVerified email at harvard.edu
Behnam NeyshaburSenior Staff Research Scientist, DeepMindVerified email at google.com
Anders Johan AndreassenGoogleVerified email at google.com
Ellen VitercikStanford UniversityVerified email at stanford.edu
Colin WhiteAbacus.AIVerified email at cs.cmu.edu
Yiding JiangPhD Student, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Christina BaekPhD Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Greg GangerJatras Professor, Carnegie Mellon UniversityVerified email at ece.cmu.edu
Saurabh KadekodiResearch Scientist, Google Inc.Verified email at google.com
Colin RaffelUniversity of Toronto, Vector Institute and Hugging FaceVerified email at cs.toronto.edu
Ian GoodfellowDeepMindVerified email at deepmind.com
Melrose RoderickPostdoc - MilaVerified email at mila.quebec
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Arun Sai SuggalaGoogle ResearchVerified email at google.com
Adarsh PrasadPhD Student, Machine Learning Department, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
Balaraman RavindranProfessor of Computer Science, Indian Institute of Technology MadrasVerified email at cse.iitm.ac.in
Kijung ShinAssociate Professor, KAISTVerified email at kaist.ac.kr

Vaishnavh Nagarajan

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Artificial Intelligence Learning Theory Deep Learning Generative Models


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Gradient descent GAN optimization is locally stable V Nagarajan, JZ Kolter Advances in Neural Information Processing Systems, 5585-5595, 2017	373	2017
Uniform convergence may be unable to explain generalization in deep learning V Nagarajan, JZ Kolter Advances in Neural Information Processing Systems, 2019	275	2019
Understanding the Failure Modes of Out-of-Distribution Generalization V Nagarajan, A Andreassen, B Neyshabur International Conference on Learning Representations (ICLR) 2021, 2020	150	2020
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience V Nagarajan, Z Kolter International Conference on Learning Representations, 2019, 2018	107	2018
Assessing Generalization via Disagreement Y Jiang, V Nagarajan, C Baek, JZ Kolter International Conference on Learning Representations, 2022, 2021	95*	2021
Generalization in deep networks: The role of distance from initialization V Nagarajan, JZ Kolter arXiv preprint arXiv:1901.01672, 2019	87	2019
Learning-theoretic foundations of algorithm configuration for combinatorial partitioning problems MF Balcan, V Nagarajan, E Vitercik, C White Conference on Learning Theory, 213-274, 2016	59	2016
Geriatrix: Aging what you see and what you don’t see. A file system aging approach for modern storage systems S Kadekodi, V Nagarajan, GR Ganger, GA Gibson Proceedings of the 2018 USENIX Conference on Usenix Annual Technical …, 2018	43	2018
Theoretical Insights into Memorization in GANs V Nagarajan, C Raffel, IJ Goodfellow	30*
Revisiting Adversarial Risk AS Suggala, A Prasad, V Nagarajan, P Ravikumar The 22nd International Conference on Artificial Intelligence and Statistics …, 2019	28	2019
Incorporating side information in tensor completion H Lamba, V Nagarajan, K Shin, N Shajarisales Proceedings of the 25th International Conference Companion on World Wide Web …, 2016	17	2016
A Learning Theoretic Perspective on Local Explainability J Li, V Nagarajan, G Plumb, A Talwalkar International Conference on Learning Representations (ICLR) 2021, 2020	15	2020
Provably Safe PAC-MDP Exploration Using Analogies M Roderick, V Nagarajan, JZ Kolter Proceedings of the 24th International Conference on Artificial Intelligence …, 2020	12	2020
Explaining generalization in deep learning: progress and fundamental limits V Nagarajan arXiv preprint arXiv:2110.08922, 2021	10	2021
A Reinforcement learning approach to online learning of decision trees A Garlapati, A Raghunathan, V Nagarajan, B Ravindran arXiv preprint arXiv:1507.06923, 2015	9	2015
Every team deserves a second chance: Identifying when things go wrong V Nagarajan, L Soriano Marcolino, M Tambe Proceedings of the 2015 International Conference on Autonomous Agents and …, 2015	8	2015
Every team deserves a second chance: Identifying when things go wrong (student abstract version) V Nagarajan, LS Marcolino, M Tambe Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	8	2015
ResMem: Learn what you can and memorize the rest Z Yang, M Lukasik, V Nagarajan, Z Li, AS Rawat, M Zaheer, AK Menon, ... arXiv preprint arXiv:2302.01576, 2023	3	2023
Avoiding Spurious Correlations: Bridging Theory and Practice T Nguyen, V Nagarajan, H Sedghi, B Neyshabur NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and …, 2021	3	2021
Lifelong learning in costly feature spaces MF Balcan, A Blum, V Nagarajan Theoretical Computer Science 808, 14-37, 2020	2	2020

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