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Wei Deng
Wei Deng
Machine Learning Research, Morgan Stanley
Verified email at purdue.edu - Homepage
Title
Cited by
Cited by
Year
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
W Deng, X Zhang, F Liang, G Lin
Advances in Neural Information Processing Systems (NeurIPS'19), 5563-5573, 2019
282019
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving
W Deng, J Pan, T Zhou, D Kong, A Flores, G Lin
The 14th International Conference on Web Search and Data Mining (WSDM'21), 2021
27*2021
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
W Deng, Q Feng, L Gao, F Liang, G Lin
The 37th International Conference on Machine Learning (ICML'20), 2020
172020
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
W Deng, G Lin, F Liang
Advances in Neural Information Processing Systems (NeurIPS'20), 2020
82020
Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications
R Zhang, W Deng, MY Zhu
The 9th Asian Conference on Machine Learning (ACML'17), 2017
72017
Information Directed Sampling for Sparse Linear Bandits
B Hao, T Lattimore, W Deng
Advances in Neural Information Processing Systems (NeurIPS'21), 2021
52021
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
W Deng, Q Feng, G Karagiannis, G Lin, F Liang
The 9th International Conference on Learning Representations (ICLR'21), 2021
42021
Bayesian Sparse Learning with Preconditioned Stochastic Gradient MCMC and its Applications
Y Wang, W Deng, G Lin
Journal of Computational Physics, 2021
42021
On Convergence of Federated Averaging Langevin Dynamics
W Deng, Q Zhang, YA Ma, Z Song, G Lin
http://arxiv.org/abs/2112.05120, 2022
32022
An Adaptive Hessian Approximated Stochastic Gradient MCMC Method
Y Wang, W Deng, G Lin
Journal of Computational Physics, 110150, 2021
32021
Interacting Contour Stochastic Gradient Langevin Dynamics
W Deng, S Liang, B Hao, G Lin, F Liang
The 10th International Conference on Learning Representations (ICLR'22), 2022
2022
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
2022
Non-convex Bayesian Learning via Stochastic Gradient Markov Chain Monte Carlo
W Deng
Purdue University, 2021
2021
Non-reversible Parallel Tempering for Uncertainty Approximation in Deep Learning
W Deng, Q Zhang, Q Feng, F Liang, G Lin
Workshop on Distribution-Free Uncertainty Quantification at ICML 2021, 2021
2021
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Articles 1–14