Követés
Raaz Dwivedi
Raaz Dwivedi
Assistant Professor, Cornell Tech
E-mail megerősítve itt: cornell.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Log-concave sampling: Metropolis-Hastings algorithms are fast
R Dwivedi*, Y Chen*, MJ Wainwright, B Yu
Journal of Machine Learning Research (JMLR) 2019., 2018
3212018
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients
Y Chen, R Dwivedi, MJ Wainwright, B Yu
Journal of Machine Learning Research (JMLR) 2020, 2019
1312019
Fast MCMC sampling algorithms on polytopes
Y Chen*, R Dwivedi*, MJ Wainwright, B Yu
Journal of Machine Learning Research (JMLR) 2018, 2018
1012018
Curating a COVID-19 data repository and forecasting county-level death counts in the United States
N Altieri, RL Barter, J Duncan, R Dwivedi, K Kumbier, X Li, R Netzorg, ...
Harvard Data Science Review (HDSR) 2021, 2021
86*2021
Singularity, Misspecification, and the Convergence Rate of EM
R Dwivedi*, N Ho*, K Khamaru*, MJ Wainwright, MI Jordan, B Yu
Annals of Statistics (AoS) 2020, 2020
722020
Kernel thinning
R Dwivedi, L Mackey
Journal of Machine Learning Research 25 (152), 1-77, 2024
432024
Sharp Analysis of Expectation-Maximization for Weakly Identifiable Models
R Dwivedi*, N Ho*, K Khamaru*, MJ Wainwright, MI Jordan, B Yu
International Conf. on Artificial Intelligence & Statistics (AISTATS) 2020, 2019
37*2019
Stable discovery of interpretable subgroups via calibration in causal studies
R Dwivedi*, YS Tan*, B Park, M Wei, K Horgan, D Madigan, B Yu
International Statistical Review (ISR) 2020, 2020
362020
Generalized kernel thinning
R Dwivedi, L Mackey
International Conference on Learning Representations (ICLR) 2022, 2021
352021
Revisiting minimum description length complexity in overparameterized models
R Dwivedi*, C Singh*, B Yu, MJ Wainwright
Journal of Machine Learning Research (JMLR) 2023, 2023
27*2023
The power of online thinning in reducing discrepancy
R Dwivedi, ON Feldheim, O Gurel-Gurevich, A Ramdas
Probability Theory and Related Fields (PTRF) 2019, 2019
252019
Vaidya walk: A sampling algorithm based on the volumetric barrier
Y Chen*, R Dwivedi*, MJ Wainwright, B Yu
Allerton Conference on Communication, Control, & Computing 2017, 2017
222017
Distribution compression in near-linear time
A Shetty, R Dwivedi, L Mackey
International Conference on Learning Representations (ICLR) 2022, 2021
212021
Counterfactual inference for sequential experiments
R Dwivedi, K Tian, S Tomkins, P Klasnja, S Murphy, D Shah
arXiv preprint arXiv:2202.06891, 2022
192022
Compress then test: Powerful kernel testing in near-linear time
C Domingo-Enrich, R Dwivedi, L Mackey
arXiv preprint arXiv:2301.05974, 2023
182023
Theoretical guarantees for EM under misspecified Gaussian mixture models
R Dwivedi*, N Ho*, K Khamaru*, MJ Wainwright, MI Jordan
Advances in Neural Information Processing Systems (NeurIPS) 2018, 2018
182018
Instability, Computational Efficiency and Statistical Accuracy
N Ho*, K Khamaru*, R Dwivedi*, MJ Wainwright, MI Jordan, B Yu
Journal of Machine Learning Research (JMLR) 2022+, accepted with minor revision, 2020
162020
On counterfactual inference with unobserved confounding
A Shah, R Dwivedi, D Shah, GW Wornell
arXiv preprint, NeurIPS Workshop on Causality for Real-World Impact 2022, 2022
142022
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling
S Ghosh*, R Kim*, P Chhabria, R Dwivedi, P Klasnja, P Liao, K Zhang, ...
Machine Learning, 1-37, 2024
92024
Doubly robust nearest neighbors in factor models
R Dwivedi, K Tian, S Tomkins, P Klasnja, S Murphy, D Shah
arXiv preprint arXiv:2211.14297, 2022
52022
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Cikkek 1–20