Yi-An Ma

发表

On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo pdf

Michael I. Jordan, Peter L. Bartlett, Yi-An Ma, 2018, ICML.

A Complete Recipe for Stochastic Gradient MCMC

Tianqi Chen, Emily B. Fox, Yi-An Ma, 2015, NIPS.

Irreversible samplers from jump and continuous Markov processes

Lei Wu, Tianqi Chen, Emily B. Fox, 2016, Stat. Comput..

Universal ideal behavior and macroscopic work relation of linear irreversible stochastic thermodynamics

Yian Ma, Yi-An Ma, H. Qian, 2015, 1503.06232.

Sampling can be faster than optimization

Michael I. Jordan, Yi-An Ma, Nicolas Flammarion, 2018, Proceedings of the National Academy of Sciences.

A Unifying Framework for Devising Efficient and Irreversible MCMC Samplers

E. Fox, Tianqi Chen, Lei Wu, 2016 .

On Thompson Sampling with Langevin Algorithms pdf

Michael I. Jordan, Peter L. Bartlett, Aldo Pacchiano, 2020, ICML 2020.

High-Order Langevin Diffusion Yields an Accelerated MCMC Algorithm pdf

Martin J. Wainwright, Michael I. Jordan, Peter L. Bartlett, 2019, J. Mach. Learn. Res..

Is There an Analog of Nesterov Acceleration for MCMC? pdf

Michael I. Jordan, Yi-An Ma, Xiang Cheng, 2019, ArXiv.

Bayesian Robustness: A Nonasymptotic Viewpoint pdf

Anca D. Dragan, Michael I. Jordan, Peter L. Bartlett, 2019, Journal of the American Statistical Association.

RobULA: Efficient Sampling for Robust Bayesian Inference

Michael I. Jordan, P. Bartlett, A. Dragan, 2019 .

On Approximate Thompson Sampling with Langevin Algorithms

Michael I. Jordan, Peter L. Bartlett, Yi-An Ma, 2020, ICML.

Robust Calibration with Multi-domain Temperature Scaling

Michael I. Jordan, Yi-An Ma, Stephen Bates, 2022, NeurIPS.

On Convergence of Federated Averaging Langevin Dynamics

Yi-An Ma, Zhao Song, Guang Lin, 2021, ArXiv.

On Convergence of Federated Averaging Langevin Dynamics

Yi-An Ma, Zhao Song, Guang Lin, 2021, ArXiv.

Irreversible samplers from jump and continuous Markov processes

E. Fox, Lei Wu, Yi-An Ma, 2018, Statistics and Computing.

Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors

Michael W. Dusenberry, Jasper Snoek, Yeming Wen, 2020, ICML.

Deep Bayesian Active Learning for Accelerating Stochastic Simulation

A. Vespignani, Yi-An Ma, Rose Yu, 2021, 2106.02770.

Underspecification Presents Challenges for Credibility in Modern Machine Learning pdf

Alexander D'Amour, Andrea Montanari, Xiaohua Zhai, 2020, J. Mach. Learn. Res..

Variational Refinement for Importance Sampling Using the Forward Kullback-Leibler Divergence

Michael I. Jordan, Ghassen Jerfel, Katherine A. Heller, 2021, UAI.

DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting pdf

Alessandro Vespignani, Rose Yu, Matteo Chinazzi, 2021, ArXiv.

Stochastic Gradient MCMC for State Space Models

Emily B. Fox, Yi-An Ma, Nicholas J. Foti, 2018, SIAM J. Math. Data Sci..

Multi-fidelity Hierarchical Neural Processes

A. Vespignani, Yi-An Ma, Rose Yu, 2022, KDD.

Quantifying Uncertainty in Deep Spatiotemporal Forecasting

Rose Yu, Matteo Chinazzi, Alessandro Vespignani, 2021, KDD.

Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization

Yi-An Ma, T. V. Marinov, Tong Zhang, 2022, ArXiv.

When is the Convergence Time of Langevin Algorithms Dimension Independent? A Composite Optimization Viewpoint pdf

Yoav Freund, Tong Zhang, Yi-An Ma, 2021, J. Mach. Learn. Res..

Accelerating Stochastic Simulation with Spatiotemporal Neural Processes

A. Vespignani, Yi-An Ma, Rose Yu, 2022 .

Black-Box Variational Inference Converges

Yi-An Ma, Jisu Oh, Kaiwen Wu, 2023, ArXiv.

Statistical and Computational Trade-offs in Variational Inference: A Case Study in Inferential Model Selection

Nikki Lijing Kuang, Yi-An Ma, K. Bhatia, 2022, ArXiv.

On Optimal Early Stopping: Over-informative versus Under-informative Parametrization

Yi-An Ma, Ruoqi Shen, Liyao (Mars) Gao, 2022, ArXiv.

Deep Bayesian Active Learning for Accelerating Stochastic Simulation

A. Vespignani, Yi-An Ma, Rose Yu, 2021, KDD.

Disentangled Multi-Fidelity Deep Bayesian Active Learning

Yi-An Ma, Rose Yu, Ruijia Niu, 2023, ICML.

Irreversibility in Stochastic Dynamic Models and Efficient Bayesian Inference

Yi-An Ma, 2017 .

Accelerating Stochastic Simulation with Interactive Neural Processes

A. Vespignani, Yi-An Ma, Rose Yu, 2021, ArXiv.

Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning

Nikki Lijing Kuang, Yi-An Ma, Amin Karbasi, 2023, ICML.

Monte Carlo Sampling without Isoperimetry: A Reverse Diffusion Approach

T. Zhang, Yi-An Ma, Yi Hao, 2023, ArXiv.

Stochastic Gradient MCMC Methods for Hidden Markov Models

Emily B. Fox, Yi-An Ma, Nicholas J. Foti, 2017, ICML.

Estimate exponential memory decay in Hidden Markov Model and its applications

Hong Qian, Felix X.-F. Ye, Yian Ma, 2017, 1710.06078.

On the Convergence of Black-Box Variational Inference

Yi-An Ma, Jisu Oh, Kaiwen Wu, 2023, 2305.15349.

DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting

Yi-An Ma, Alessandro Vespignani, Rose Yu, 2021, ArXiv.