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Yian Ma
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2020 – today
- 2024
- [c5]Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang:
Reverse Diffusion Monte Carlo. ICLR 2024 - [c4]Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg, Zhiqi Bu:
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy. ICLR 2024 - [i4]Xunpeng Huang, Difan Zou, Hanze Dong, Yian Ma, Tong Zhang:
Faster Sampling without Isoperimetry via Diffusion-based Monte Carlo. CoRR abs/2401.06325 (2024) - [i3]Amartya Sanyal, Yaxi Hu, Yaodong Yu, Yian Ma, Yixin Wang, Bernhard Schölkopf:
Accuracy on the wrong line: On the pitfalls of noisy data for out-of-distribution generalisation. CoRR abs/2406.19049 (2024) - 2023
- [c3]Nikki Lijing Kuang, Ming Yin, Mengdi Wang, Yu-Xiang Wang, Yian Ma:
Posterior Sampling with Delayed Feedback for Reinforcement Learning with Linear Function Approximation. NeurIPS 2023 - [i2]Xunpeng Huang, Hanze Dong, Yifan Hao, Yian Ma, Tong Zhang:
Monte Carlo Sampling without Isoperimetry: A Reverse Diffusion Approach. CoRR abs/2307.02037 (2023) - [i1]Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg:
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy. CoRR abs/2310.14661 (2023) - 2021
- [c2]Ghassen Jerfel, Serena Lutong Wang, Clara Wong-Fannjiang, Katherine A. Heller, Yian Ma, Michael I. Jordan:
Variational refinement for importance sampling using the forward Kullback-Leibler divergence. UAI 2021: 1819-1829 - 2020
- [c1]Matthew D. Hoffman, Yian Ma:
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics. ICML 2020: 4324-4341
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last updated on 2024-08-10 01:24 CEST by the dblp team
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