Nilesh Tripuraneni

32 papers A* 12Journal 17Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Choosing a Proxy Metric from Past Experiments. KDD Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour, Jacopo Soriano, Steve Yadlowsky
2024	J	`jnl`	Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. CoRR Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, Rohan Anil, Ethan Dyer, Siamak Shakeri, Roopali Vij, Harsh Mehta, Vinay V. Ramasesh, Quoc Le, Ed H. Chi, Yifeng Lu, Orhan Firat, Angeliki Lazaridou, Jean-Baptiste Lespiau, Nithya Attaluri, Kate Olszewska
2023	J	`jnl`	Choosing a Proxy Metric from Past Experiments. CoRR Nilesh Tripuraneni, Lee Richardson, Alexander D'Amour, Jacopo Soriano, Steve Yadlowsky
2023	J	`jnl`	Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models. CoRR Steve Yadlowsky, Lyric Doshi, Nilesh Tripuraneni
2022	J	`jnl`	Joint Representation Training in Sequential Tasks with Shared Structure. CoRR Aldo Pacchiano, Ofir Nachum, Nilesh Tripuraneni, Peter L. Bartlett
2022	—	`—`	Learning Beyond the Standard Model (of Data) Nilesh Tripuraneni
2022	A*	`conf`	Optimal Mean Estimation without a Variance. COLT Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter L. Bartlett, Michael I. Jordan
2021	J	`jnl`	Covariate Shift in High-Dimensional Random Feature Regression. CoRR Nilesh Tripuraneni, Ben Adlam, Jeffrey Pennington
2021	A*	`conf`	Overparameterization Improves Robustness to Covariate Shift in High Dimensions. NeurIPS Nilesh Tripuraneni, Ben Adlam, Jeffrey Pennington
2021	J	`jnl`	Parallelizing Contextual Linear Bandits. CoRR Jeffrey Chan, Aldo Pacchiano, Nilesh Tripuraneni, Yun S. Song, Peter L. Bartlett, Michael I. Jordan
2021	A*	`conf`	Provable Meta-Learning of Linear Representations. ICML Nilesh Tripuraneni, Chi Jin, Michael I. Jordan
2020	A*	`conf`	Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond. STOC Yeshwanth Cherapanamjeri, Samuel B. Hopkins, Tarun Kathuria, Prasad Raghavendra, Nilesh Tripuraneni
2020	A*	`conf`	On the Theory of Transfer Learning: The Importance of Task Diversity. NeurIPS Nilesh Tripuraneni, Michael I. Jordan, Chi Jin
2020	J	`jnl`	On the Theory of Transfer Learning: The Importance of Task Diversity. CoRR Nilesh Tripuraneni, Michael I. Jordan, Chi Jin
2020	J	`jnl`	Optimal Mean Estimation without a Variance. CoRR Yeshwanth Cherapanamjeri, Nilesh Tripuraneni, Peter L. Bartlett, Michael I. Jordan
2020	J	`jnl`	Optimal Robust Linear Regression in Nearly Linear Time. CoRR Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni, Michael I. Jordan, Nicolas Flammarion, Peter L. Bartlett
2020	J	`jnl`	Provable Meta-Learning of Linear Representations. CoRR Nilesh Tripuraneni, Chi Jin, Michael I. Jordan
2020	A*	`conf`	Single Point Transductive Prediction. ICML Nilesh Tripuraneni, Lester Mackey
2019	J	`jnl`	Algorithms for Heavy-Tailed Statistics: Regression, Covariance Estimation, and Beyond. CoRR Yeshwanth Cherapanamjeri, Samuel B. Hopkins, Tarun Kathuria, Prasad Raghavendra, Nilesh Tripuraneni
2019	J	`jnl`	Debiasing Linear Prediction. CoRR Nilesh Tripuraneni, Lester Mackey
2019	A*	`conf`	Rao-Blackwellized Stochastic Gradients for Discrete Distributions. ICML Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni, Michael I. Jordan, Jon D. McAuliffe
2018	A*	`conf`	Averaging Stochastic Gradient Descent on Riemannian Manifolds. COLT Nilesh Tripuraneni, Nicolas Flammarion, Francis R. Bach, Michael I. Jordan
2018	J	`jnl`	Averaging Stochastic Gradient Descent on Riemannian Manifolds. CoRR Nilesh Tripuraneni, Nicolas Flammarion, Francis R. Bach, Michael I. Jordan
2018	J	`jnl`	Rao-Blackwellized Stochastic Gradients for Discrete Distributions. CoRR Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni, Michael I. Jordan, Jon McAuliffe
2018	A*	`conf`	Stochastic Cubic Regularization for Fast Nonconvex Optimization. NeurIPS Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan
2017	A*	`conf`	Lost Relatives of the Gumbel Trick. ICML Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller
2017	J	`jnl`	Lost Relatives of the Gumbel Trick. CoRR Matej Balog, Nilesh Tripuraneni, Zoubin Ghahramani, Adrian Weller
2017	A*	`conf`	Magnetic Hamiltonian Monte Carlo. ICML Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani, Richard E. Turner
2017	J	`jnl`	Quantitative criticism of literary relationships. Proc. Natl. Acad. Sci. USA Joseph P. Dexter, Theodore Katz, Nilesh Tripuraneni, Tathagata Dasgupta, Ajay Kannan, James Brofos, Jorge A. Bonilla Lopez, Lea A. Schroeder, Adriana Casarez, Maxim Rabinovich, Ayelet Haimson Lushkov, Pramit Chaudhuri
2017	J	`jnl`	Stochastic Cubic Regularization for Fast Nonconvex Optimization. CoRR Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan
2015	—	`conf`	Particle Gibbs for Infinite Hidden Markov Models. NIPS Nilesh Tripuraneni, Shixiang Gu, Hong Ge, Zoubin Ghahramani
2013	—	`conf`	Evaluating Stream Filtering for Entity Profile Updates for TREC 2013. TREC John R. Frank, Steven J. Bauer, Max Kleiman-Weiner, Daniel A. Roberts, Nilesh Tripuraneni, Ce Zhang, Christopher Ré, Ellen M. Voorhees, Ian Soboroff