Raaz Dwivedi

According to our database, Raaz Dwivedi authored at least 28 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling.

Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag Klasnja, Peng Liao, Kelly W. Zhang, Susan A. Murphy

Mach. Learn., July, 2024

Kernel Thinning.

Raaz Dwivedi, Lester Mackey

J. Mach. Learn. Res., 2024

Supervised Kernel Thinning.

Albert Gong, Kyuseong Choi, Raaz Dwivedi

CoRR, 2024

Learning Counterfactual Distributions via Kernel Nearest Neighbors.

Kyuseong Choi, Jacob Feitelberg, Anish Agarwal, Raaz Dwivedi

CoRR, 2024

Distributional Matrix Completion via Nearest Neighbors in the Wasserstein Space.

Jacob Feitelberg, Kyuseong Choi, Anish Agarwal, Raaz Dwivedi

CoRR, 2024

FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations.

Jane Dwivedi-Yu, Raaz Dwivedi, Timo Schick

CoRR, 2024

Doubly Robust Inference in Causal Latent Factor Models.

Alberto Abadie, Anish Agarwal, Raaz Dwivedi, Abhin Shah

CoRR, 2024

Debiased Distribution Compression.

Lingxiao Li, Raaz Dwivedi, Lester Mackey

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Revisiting minimum description length complexity in overparameterized models.

Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright

J. Mach. Learn. Res., 2023

Compress Then Test: Powerful Kernel Testing in Near-linear Time.

Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Doubly robust nearest neighbors in factor models.

Raaz Dwivedi, Katherine Tian, Sabina Tomkins, Predrag V. Klasnja, Susan A. Murphy, Devavrat Shah

CoRR, 2022

On counterfactual inference with unobserved confounding.

Abhin Shah, Raaz Dwivedi, Devavrat Shah, Gregory W. Wornell

CoRR, 2022

Counterfactual inference for sequential experimental design.

Raaz Dwivedi, Susan A. Murphy, Devavrat Shah

CoRR, 2022

Distribution Compression in Near-Linear Time.

Abhishek Shetty, Raaz Dwivedi, Lester Mackey

Proceedings of the Tenth International Conference on Learning Representations, 2022

Generalized Kernel Thinning.

Raaz Dwivedi, Lester Mackey

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Principled Statistical Approaches For Sampling and Inference in High Dimensions

Raaz Dwivedi

PhD thesis, 2021

2020

Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients.

Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

J. Mach. Learn. Res., 2020

Stable discovery of interpretable subgroups via calibration in causal studies.

Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu

CoRR, 2020

Revisiting complexity and the bias-variance tradeoff.

Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright

CoRR, 2020

Instability, Computational Efficiency and Statistical Accuracy.

Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu

CoRR, 2020

Curating a COVID-19 data repository and forecasting county-level death counts in the United States.

Nick Altieri, Rebecca L. Barter, James Duncan, Raaz Dwivedi, Karl Kumbier, Xiao Li, Robert Netzorg, Briton Park, Chandan Singh, Yan Shuo Tan, Tiffany M. Tang, Yu Wang, Bin Yu

CoRR, 2020

Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models.

Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Log-concave sampling: Metropolis-Hastings algorithms are fast.

Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu

J. Mach. Learn. Res., 2019

Challenges with EM in application to weakly identifiable mixture models.

Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu

CoRR, 2019

2018

Fast MCMC Sampling Algorithms on Polytopes.

Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

J. Mach. Learn. Res., 2018

Theoretical guarantees for EM under misspecified Gaussian mixture models.

Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Vaidya walk: A sampling algorithm based on the volumetric barrier.

Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016

Gaussian approximations in high dimensional estimation.

Vivek S. Borkar, Raaz Dwivedi, Neeraja Sahasrabudhe

Syst. Control. Lett., 2016