Nilesh Tripuraneni

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Chi JinAssistant Professor, Princeton UniversityVerified email at princeton.edu
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Jeffrey RegierAssistant Professor, Department of Statistics, University of MichiganVerified email at umich.edu
Yeshwanth CherapanamjeriPh.D Student, UC BerkeleyVerified email at berkeley.edu
Nicolas FlammarionEPFLVerified email at epfl.ch
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Mitchell SternUC BerkeleyVerified email at berkeley.edu
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Jeffrey PenningtonGoogle BrainVerified email at google.com
Ben AdlamGoogle BrainVerified email at google.com
Pramit ChaudhuriAssociate Professor of Classics, The University of Texas at AustinVerified email at austin.utexas.edu
Mark RowlandResearch Scientist, DeepMindVerified email at google.com
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk
Jon McAuliffeProfessor (Adj.) of Statistics, University of California, BerkeleyVerified email at stat.berkeley.edu
Samuel B. HopkinsMassachusetts Institute of TechnologyVerified email at mit.edu
Matej BalogResearch Scientist, DeepMindVerified email at google.com
Adrian WellerDirector of Research, Machine Learning, University of CambridgeVerified email at eng.cam.ac.uk
Shixiang Shane GuOpenAIVerified email at openai.com
Joseph DexterData Science Initiative and Department of Human Evolutionary Biology, Harvard UniversityVerified email at fas.harvard.edu

Nilesh Tripuraneni

UC Berkeley

Verified email at berkeley.edu - Homepage

Machine Learning Statistics Optimization Artificial Intelligence


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Stochastic cubic regularization for fast nonconvex optimization N Tripuraneni, M Stern, C Jin, J Regier, MI Jordan Advances in neural information processing systems 31, 2018	149	2018
Provable meta-learning of linear representations N Tripuraneni, C Jin, M Jordan International Conference on Machine Learning, 10434-10443, 2021	103	2021
Bulk viscosity and cavitation in boost-invariant hydrodynamic expansion K Rajagopal, N Tripuraneni Journal of High Energy Physics 2010 (3), 1-28, 2010	103	2010
On the theory of transfer learning: The importance of task diversity N Tripuraneni, M Jordan, C Jin Advances in neural information processing systems 33, 7852-7862, 2020	99	2020
Averaging stochastic gradient descent on Riemannian manifolds N Tripuraneni, N Flammarion, F Bach, MI Jordan Conference On Learning Theory, 650-687, 2018	87	2018
Magnetic hamiltonian monte carlo N Tripuraneni, M Rowland, Z Ghahramani, R Turner International Conference on Machine Learning, 3453-3461, 2017	38	2017
Algorithms for heavy-tailed statistics: Regression, covariance estimation, and beyond Y Cherapanamjeri, SB Hopkins, T Kathuria, P Raghavendra, ... Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing …, 2020	32	2020
Rao-Blackwellized stochastic gradients for discrete distributions R Liu, J Regier, N Tripuraneni, M Jordan, J Mcauliffe International Conference on Machine Learning, 4023-4031, 2019	32	2019
Optimal robust linear regression in nearly linear time Y Cherapanamjeri, E Aras, N Tripuraneni, MI Jordan, N Flammarion, ... arXiv preprint arXiv:2007.08137, 2020	30	2020
Lost relatives of the Gumbel trick M Balog, N Tripuraneni, Z Ghahramani, A Weller International Conference on Machine Learning, 371-379, 2017	23	2017
Particle Gibbs for infinite hidden Markov models N Tripuraneni, SS Gu, H Ge, Z Ghahramani Advances in Neural Information Processing Systems 28, 2015	23	2015
Quantitative criticism of literary relationships JP Dexter, T Katz, N Tripuraneni, T Dasgupta, A Kannan, JA Brofos, ... Proceedings of the National Academy of Sciences 114 (16), E3195-E3204, 2017	19	2017
Overparameterization improves robustness to covariate shift in high dimensions N Tripuraneni, B Adlam, J Pennington Advances in Neural Information Processing Systems 34, 13883-13897, 2021	18	2021
Covariate shift in high-dimensional random feature regression N Tripuraneni, B Adlam, J Pennington arXiv preprint arXiv:2111.08234, 2021	12	2021
Optimal mean estimation without a variance Y Cherapanamjeri, N Tripuraneni, P Bartlett, M Jordan Conference on Learning Theory, 356-357, 2022	11	2022
Single point transductive prediction N Tripuraneni, L Mackey International Conference on Machine Learning, 9593-9602, 2020	7*	2020
Parallelizing contextual linear bandits J Chan, A Pacchiano, N Tripuraneni, YS Song, P Bartlett, MI Jordan arXiv preprint arXiv:2105.10590, 2021	6	2021
Assessment of Treatment Effect Estimators for Heavy-Tailed Data N Tripuraneni, D Madeka, D Foster, D Perrault-Joncas, MI Jordan arXiv preprint arXiv:2112.07602, 2021	2	2021
Learning Beyond the Standard Model (of Data) N Tripuraneni UC Berkeley, 2022		2022
Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data N Tripuraneni, D Madeka, D Foster, D Perrault-Joncas, MI Jordan arXiv e-prints, arXiv: 2112.07602, 2021		2021

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