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Wei Deng
Wei Deng
Researcher at Morgan Stanley
Verified email at purdue.edu - Homepage
Title
Cited by
Cited by
Year
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving
W Deng, J Pan, T Zhou, D Kong, A Flores, G Lin
WSDM'21, 2021
812021
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
W Deng, X Zhang, F Liang, G Lin
NeurIPS'19, 2019
502019
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
W Deng, Q Feng, L Gao, F Liang, G Lin
ICML'20, 2020
492020
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
W Deng, G Lin, F Liang
NeurIPS'20, 2020
282020
On Convergence of Federated Averaging Langevin Dynamics
W Deng, Q Zhang, YA Ma, Z Song, G Lin
UAI'24, 2024
192024
Information Directed Sampling for Sparse Linear Bandits
B Hao, T Lattimore, W Deng
NeurIPS'21, 2021
192021
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
Y Chen, W Deng, S Fang, F Li, NT Yang, Y Zhang, K Rasul, S Zhe, ...
ICML'23, 2023
182023
An Adaptively Weighted Stochastic Gradient MCMC Algorithm for Monte Carlo simulation and Global Optimization
W Deng, G Lin, F Liang
Statistics and Computing 32 (58), 1-24, 2022
142022
Interacting Contour Stochastic Gradient Langevin Dynamics
W Deng, S Liang, B Hao, G Lin, F Liang
ICLR'22, 2022
132022
Bayesian Sparse Learning with Preconditioned Stochastic Gradient MCMC and its Applications
Y Wang, W Deng, G Lin
Journal of Computational Physics, 2021
122021
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications
R Zhang, W Deng, MY Zhu
ACML'17, 2017
72017
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
W Deng, Q Feng, G Karagiannis, G Lin, F Liang
ICLR'21, 2021
62021
An Adaptive Hessian Approximated Stochastic Gradient MCMC Method
Y Wang, W Deng, G Lin
Journal of Computational Physics, 110150, 2021
52021
Reflected Schrödinger Bridge for Constrained Generative Modeling
W Deng, Y Chen, NT Yang, H Du, Q Feng, RTQ Chen
UAI'24, 2024
42024
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
H Zheng, W Deng, C Moya, G Lin
AISTATS'24, 2024
32024
Non-reversible Parallel Tempering for Deep Posterior Approximation
W Deng, Q Zhang, Q Feng, F Liang, G Lin
AAAI'23, 2023
32023
On Convergence of Approximate Schrödinger Bridge with Bounded Cost
W Deng, Y Chen, NT Yang, H Du, Q Feng, RTQ Chen
Learning, Control, and Dynamical Systems Workshop (ICML'23 Workshop), 2023
12023
Batch Normalization Preconditioning for Stochastic Gradient Langevin Dynamics
S Lange, W Deng, Q Ye, G Lin
JML, 2023
12023
Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory
J Liang, Q Zhang, W Deng, Q Song, G Lin
Journal of Computational and Graphical Statistics, 2024
2024
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
H Zheng, H Du, Q Feng, W Deng, G Lin
ICML'24, 2024
2024
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