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1512.07666
Cited By
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks
23 December 2015
Chunyuan Li
Changyou Chen
David Carlson
Lawrence Carin
ODL
BDL
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Papers citing
"Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks"
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Title
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Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
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Deep Autoencoding Topic Model with Scalable Hybrid Bayesian Inference
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AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC
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Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients
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DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving
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Robust Reinforcement Learning via Adversarial training with Langevin Dynamics
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Estimating Uncertainty Intervals from Collaborating Networks
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Extended Stochastic Gradient MCMC for Large-Scale Bayesian Variable Selection
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Differential Bayesian Neural Nets
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Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo
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Difan Zou
Quanquan Gu
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Thompson Sampling via Local Uncertainty
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Stein Variational Gradient Descent With Matrix-Valued Kernels
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An Adaptive Empirical Bayesian Method for Sparse Deep Learning
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Xiao Zhang
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Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics
AAAI Conference on Artificial Intelligence (AAAI), 2019
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Chaochao Chen
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Cen Chen
Xingtai Lv
Guangyu Sun
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Deep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective
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Variationally Inferred Sampling Through a Refined Bound for Probabilistic Programs
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Bayesian Inference for Large Scale Image Classification
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Mini-batch Metropolis-Hastings MCMC with Reversible SGLD Proposal
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Y. X. R. Wang
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Adaptively Preconditioned Stochastic Gradient Langevin Dynamics
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Function Space Particle Optimization for Bayesian Neural Networks
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Zhaolin Ren
Jun Zhu
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Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
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