Cikkek nyilvánosan hozzáférhető megbízással - Raaz DwivediTovábbi információ
Valahol hozzáférhető: 11
Log-concave sampling: Metropolis-Hastings algorithms are fast
R Dwivedi*, Y Chen*, MJ Wainwright, B Yu
Journal of Machine Learning Research (JMLR) 2019., 2018
Megbízások: US National Science Foundation, US Department of Defense
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
Megbízások: US National Science Foundation, US Department of Defense
Fast MCMC sampling algorithms on polytopes
Y Chen*, R Dwivedi*, MJ Wainwright, B Yu
Journal of Machine Learning Research (JMLR) 2018, 2018
Megbízások: US National Science Foundation, US Department of Defense
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
Megbízások: US National Science Foundation, US Department of Defense
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
Megbízások: US National Science Foundation, US Department of Defense
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
Megbízások: US National Science Foundation, US Department of Defense, Chan Zuckerberg …
Revisiting minimum description length complexity in overparameterized models
R Dwivedi*, C Singh*, B Yu, MJ Wainwright
Journal of Machine Learning Research (JMLR) 2023, 2023
Megbízások: US National Science Foundation, US Department of Defense
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
Megbízások: US National Science Foundation
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
Megbízások: US National Science Foundation, US Department of Defense
Gaussian approximations in high dimensional estimation
VS Borkar, R Dwivedi, N Sahasrabudhe
Systems & Control Letters 92, 42-45, 2016
Megbízások: Department of Science & Technology, India
Removing sampling bias in networked stochastic approximation
R Dwivedi, VS Borkar
2014 International Conference on Signal Processing and Communications (SPCOM …, 2014
Megbízások: Department of Science & Technology, India
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