Nilesh Tripuraneni

Orcid: 0009-0006-9133-2984

According to our database1, Nilesh Tripuraneni authored at least 23 papers between 2013 and 2024.

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Bibliography

2024
Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries.
CoRR, 2024

Choosing a Proxy Metric from Past Experiments.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

2023
Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models.
CoRR, 2023

2022
Learning Beyond the Standard Model (of Data)
PhD thesis, 2022

Joint Representation Training in Sequential Tasks with Shared Structure.
CoRR, 2022

Optimal Mean Estimation without a Variance.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021
Covariate Shift in High-Dimensional Random Feature Regression.
CoRR, 2021

Parallelizing Contextual Linear Bandits.
CoRR, 2021

Overparameterization Improves Robustness to Covariate Shift in High Dimensions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provable Meta-Learning of Linear Representations.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Optimal Robust Linear Regression in Nearly Linear Time.
CoRR, 2020

Algorithms for heavy-tailed statistics: regression, covariance estimation, and beyond.
Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, 2020

On the Theory of Transfer Learning: The Importance of Task Diversity.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Single Point Transductive Prediction.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Debiasing Linear Prediction.
CoRR, 2019

Rao-Blackwellized Stochastic Gradients for Discrete Distributions.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Stochastic Cubic Regularization for Fast Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Averaging Stochastic Gradient Descent on Riemannian Manifolds.
Proceedings of the Conference On Learning Theory, 2018

2017
Quantitative criticism of literary relationships.
Proc. Natl. Acad. Sci. USA, 2017

Magnetic Hamiltonian Monte Carlo.
Proceedings of the 34th International Conference on Machine Learning, 2017

Lost Relatives of the Gumbel Trick.
Proceedings of the 34th International Conference on Machine Learning, 2017

2015
Particle Gibbs for Infinite Hidden Markov Models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013
Evaluating Stream Filtering for Entity Profile Updates for TREC 2013.
Proceedings of The Twenty-Second Text REtrieval Conference, 2013


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