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ORCIDRaaz Dwivedi
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Books and Theses
- 2021
[b1]Raaz Dwivedi:
Principled Statistical Approaches For Sampling and Inference in High Dimensions. University of California, Berkeley, USA, 2021
Journal Articles
- 2024
- [j7]Raaz Dwivedi, Lester Mackey:
Kernel Thinning. J. Mach. Learn. Res. 25: 152:1-152:77 (2024) - [j6]Susobhan Ghosh
, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag Klasnja, Peng Liao, Kelly W. Zhang, Susan A. Murphy:
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. Mach. Learn. 113(7): 3961-3997 (2024) - 2023
- [j5]Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright:
Revisiting minimum description length complexity in overparameterized models. J. Mach. Learn. Res. 24: 268:1-268:59 (2023) - 2020
- [j4]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients. J. Mach. Learn. Res. 21: 92:1-92:72 (2020) - 2019
- [j3]Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu:
Log-concave sampling: Metropolis-Hastings algorithms are fast. J. Mach. Learn. Res. 20: 183:1-183:42 (2019) - 2018
- [j2]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Fast MCMC Sampling Algorithms on Polytopes. J. Mach. Learn. Res. 19: 55:1-55:86 (2018) - 2016
- [j1]Vivek S. Borkar, Raaz Dwivedi, Neeraja Sahasrabudhe:
Gaussian approximations in high dimensional estimation. Syst. Control. Lett. 92: 42-45 (2016)
Conference and Workshop Papers
- 2024
- [c9]Lingxiao Li, Raaz Dwivedi, Lester Mackey:
Debiased Distribution Compression. ICML 2024 - 2023
- [c8]Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey:
Compress Then Test: Powerful Kernel Testing in Near-linear Time. AISTATS 2023: 1174-1218 - 2022
- [c7]Raaz Dwivedi, Lester Mackey:
Generalized Kernel Thinning. ICLR 2022 - [c6]Abhishek Shetty, Raaz Dwivedi, Lester Mackey:
Distribution Compression in Near-Linear Time. ICLR 2022 - 2021
- [c5]Raaz Dwivedi, Lester Mackey:
Kernel Thinning. COLT 2021: 1753 - 2020
- [c4]Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu:
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models. AISTATS 2020: 1866-1876 - 2018
- [c3]Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright, Bin Yu:
Log-concave sampling: Metropolis-Hastings algorithms are fast! COLT 2018: 793-797 - [c2]Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan:
Theoretical guarantees for EM under misspecified Gaussian mixture models. NeurIPS 2018: 9704-9712 - 2017
- [c1]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Vaidya walk: A sampling algorithm based on the volumetric barrier. Allerton 2017: 1220-1227
Informal and Other Publications
- 2024
- [i17]Alberto Abadie, Anish Agarwal, Raaz Dwivedi, Abhin Shah:
Doubly Robust Inference in Causal Latent Factor Models. CoRR abs/2402.11652 (2024) - [i16]Jane Dwivedi-Yu, Raaz Dwivedi, Timo Schick:
FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations. CoRR abs/2404.06619 (2024) - [i15]Lingxiao Li, Raaz Dwivedi, Lester Mackey:
Debiased Distribution Compression. CoRR abs/2404.12290 (2024) - 2023
- [i14]Carles Domingo-Enrich, Raaz Dwivedi, Lester Mackey:
Compress Then Test: Powerful Kernel Testing in Near-linear Time. CoRR abs/2301.05974 (2023) - [i13]Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag V. Klasnja, Peng Liao, Kelly W. Zhang, Susan A. Murphy:
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. CoRR abs/2304.05365 (2023) - 2022
- [i12]Raaz Dwivedi, Susan A. Murphy, Devavrat Shah:
Counterfactual inference for sequential experimental design. CoRR abs/2202.06891 (2022) - [i11]Abhin Shah, Raaz Dwivedi, Devavrat Shah, Gregory W. Wornell:
On counterfactual inference with unobserved confounding. CoRR abs/2211.08209 (2022) - [i10]Raaz Dwivedi, Katherine Tian, Sabina Tomkins, Predrag V. Klasnja, Susan A. Murphy, Devavrat Shah:
Doubly robust nearest neighbors in factor models. CoRR abs/2211.14297 (2022) - 2021
- [i9]Raaz Dwivedi, Lester Mackey:
Kernel Thinning. CoRR abs/2105.05842 (2021) - [i8]Raaz Dwivedi, Lester Mackey:
Generalized Kernel Thinning. CoRR abs/2110.01593 (2021) - [i7]Abhishek Shetty, Raaz Dwivedi, Lester Mackey:
Distribution Compression in Near-linear Time. CoRR abs/2111.07941 (2021) - 2020
- [i6]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:
Curating a COVID-19 data repository and forecasting county-level death counts in the United States. CoRR abs/2005.07882 (2020) - [i5]Nhat Ho, Koulik Khamaru, Raaz Dwivedi, Martin J. Wainwright, Michael I. Jordan, Bin Yu:
Instability, Computational Efficiency and Statistical Accuracy. CoRR abs/2005.11411 (2020) - [i4]Raaz Dwivedi, Chandan Singh, Bin Yu, Martin J. Wainwright:
Revisiting complexity and the bias-variance tradeoff. CoRR abs/2006.10189 (2020) - [i3]Raaz Dwivedi, Yan Shuo Tan, Briton Park, Mian Wei, Kevin Horgan, David Madigan, Bin Yu:
Stable discovery of interpretable subgroups via calibration in causal studies. CoRR abs/2008.10109 (2020) - 2019
- [i2]Raaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu:
Challenges with EM in application to weakly identifiable mixture models. CoRR abs/1902.00194 (2019) - [i1]Yuansi Chen, Raaz Dwivedi, Martin J. Wainwright, Bin Yu:
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients. CoRR abs/1905.12247 (2019)
Coauthor Index
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