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
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Yeshwanth CherapanamjeriPh.D Student, UC BerkeleyVerified email at berkeley.edu
Nicolas FlammarionEPFLVerified email at epfl.ch
Mitchell SternUC BerkeleyVerified email at berkeley.edu
Jeffrey PenningtonGoogle BrainVerified email at google.com
Francis BachInria - Ecole Normale SupérieureVerified email at inria.fr
Shixiang Shane GuGoogle DeepMindVerified email at google.com
Samuel B. HopkinsMassachusetts Institute of TechnologyVerified email at mit.edu
Prasad RaghavendraProfessor, University of California BerkeleyVerified email at cs.berkeley.edu
Mark RowlandResearch Scientist, Google DeepMindVerified email at google.com
Jon McAuliffeProfessor (Adj.) of Statistics, University of California, BerkeleyVerified email at stat.berkeley.edu
Aldo PacchianoBroad Institute of MIT and HarvardVerified email at broadinstitute.org
Matej BalogResearch Scientist, DeepMindVerified email at google.com
Adrian WellerDirector of Research, Machine Learning, University of CambridgeVerified email at eng.cam.ac.uk
Dean FosterAmazon, NYCVerified email at amazon.com

Nilesh Tripuraneni

Google DeepMind

Verified email at google.com - Homepage

Machine Learning Statistics Optimization Large Language Models Multimodal Models


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Gemini: a family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023	1493	2023
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ... arXiv preprint arXiv:2403.05530, 2024	361	2024
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	226	2020
Provable meta-learning of linear representations N Tripuraneni, C Jin, M Jordan International Conference on Machine Learning, 10434-10443, 2021	196	2021
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	189	2018
Averaging stochastic gradient descent on Riemannian manifolds N Tripuraneni, N Flammarion, F Bach, MI Jordan Conference On Learning Theory, 650-687, 2018	117	2018
Bulk viscosity and cavitation in boost-invariant hydrodynamic expansion K Rajagopal, N Tripuraneni Journal of High Energy Physics 2010 (3), 1-28, 2010	72	2010
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	52	2021
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	48	2020
Magnetic hamiltonian monte carlo N Tripuraneni, M Rowland, Z Ghahramani, R Turner International Conference on Machine Learning, 3453-3461, 2017	44	2017
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	42	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	37	2020
Lost relatives of the Gumbel trick M Balog, N Tripuraneni, Z Ghahramani, A Weller International Conference on Machine Learning, 371-379, 2017	33	2017
Covariate shift in high-dimensional random feature regression N Tripuraneni, B Adlam, J Pennington arXiv preprint arXiv:2111.08234, 2021	27	2021
Particle Gibbs for infinite hidden Markov models N Tripuraneni, SS Gu, H Ge, Z Ghahramani Advances in Neural Information Processing Systems 28, 2015	27	2015
Optimal mean estimation without a variance Y Cherapanamjeri, N Tripuraneni, P Bartlett, M Jordan Conference on Learning Theory, 356-357, 2022	26	2022
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	26	2017
Evaluating Stream Filtering for Entity Profile Updates for TREC 2013. JR Frank, SJ Bauer, M Kleiman-Weiner, DA Roberts, N Tripuraneni, ... TREC 2013, 21, 2013	25	2013
Pretraining data mixtures enable narrow model selection capabilities in transformer models S Yadlowsky, L Doshi, N Tripuraneni arXiv preprint arXiv:2311.00871, 2023	24	2023
Parallelizing contextual bandits J Chan, A Pacchiano, N Tripuraneni, YS Song, P Bartlett, MI Jordan arXiv preprint arXiv:2105.10590, 2021	13	2021

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