Tripuraneni, Nilesh

14 publications

NeurIPSW 2023 Can Transformer Models Generalize via In-Context Learning Beyond Pretraining Data? Steve Yadlowsky, Lyric Doshi, Nilesh Tripuraneni

NeurIPSW 2023 Can Transformers In-Context Learn Task Mixtures? Nilesh Tripuraneni, Lyric Doshi, Steve Yadlowsky

NeurIPSW 2023 Meta-Analysis of Randomized Experiments with Applications to Heavy-Tailed Response Data Nilesh Tripuraneni, Dominique Perrault-Joncas, Dhruv Madeka, Dean Foster, Michael Jordan

COLT 2022 Optimal Mean Estimation Without a Variance Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter Bartlett, Michael Jordan

NeurIPS 2021 Overparameterization Improves Robustness to Covariate Shift in High Dimensions Nilesh Tripuraneni, Ben Adlam, Jeffrey Pennington

ICML 2021 Provable Meta-Learning of Linear Representations Nilesh Tripuraneni, Chi Jin, Michael Jordan

NeurIPS 2020 On the Theory of Transfer Learning: The Importance of Task Diversity Nilesh Tripuraneni, Michael I. Jordan, Chi Jin

ICML 2020 Single Point Transductive Prediction Nilesh Tripuraneni, Lester Mackey

ICML 2019 Rao-Blackwellized Stochastic Gradients for Discrete Distributions Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni, Michael Jordan, Jon Mcauliffe

COLT 2018 Averaging Stochastic Gradient Descent on Riemannian Manifolds Nilesh Tripuraneni, Nicolas Flammarion, Francis R. Bach, Michael I. Jordan

NeurIPS 2018 Stochastic Cubic Regularization for Fast Nonconvex Optimization Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I Jordan

ICML 2017 Lost Relatives of the Gumbel Trick Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller

ICML 2017 Magnetic Hamiltonian Monte Carlo Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani, Richard Turner

NeurIPS 2015 Particle Gibbs for Infinite Hidden Markov Models Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani