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05/30/2023
Non-convex Bayesian Learning via Stochastic Gradient Markov Chain Monte Carlo
The rise of artificial intelligence (AI) hinges on the efficient trainin...
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05/12/2023
Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation
The Schrödinger bridge problem (SBP) is gaining increasing attention in ...
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11/20/2022
Non-reversible Parallel Tempering for Deep Posterior Approximation
Parallel tempering (PT), also known as replica exchange, is the go-to wo...
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02/20/2022
Interacting Contour Stochastic Gradient Langevin Dynamics
We propose an interacting contour stochastic gradient Langevin dynamics ...
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12/23/2021
Adversarial Attacks against Windows PE Malware Detection: A Survey of the State-of-the-Art
The malware has been being one of the most damaging threats to computers...
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12/09/2021
On Convergence of Federated Averaging Langevin Dynamics
We propose a federated averaging Langevin algorithm (FA-LD) for uncertai...
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05/29/2021
Information Directed Sampling for Sparse Linear Bandits
Stochastic sparse linear bandits offer a practical model for high-dimens...
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11/01/2020
On the Distribution of SINR for MIMO Systems with Widely Linear MMSE Receivers
The widely linear least mean square error (WLMMSE) receiver has been an ...
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10/19/2020
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
We propose an adaptively weighted stochastic gradient Langevin dynamics ...
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10/03/2020
An adaptive Hessian approximated stochastic gradient MCMC method
Bayesian approaches have been successfully integrated into training deep...
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10/02/2020
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
Replica exchange stochastic gradient Langevin dynamics (reSGLD) has show...
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08/12/2020
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
Replica exchange Monte Carlo (reMC), also known as parallel tempering, i...
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06/29/2020
Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications
In this work, we propose a Bayesian type sparse deep learning algorithm....
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02/17/2020
A Sparse Deep Factorization Machine for Efficient CTR prediction
Click-through rate (CTR) prediction is a crucial task in online display ...
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10/23/2019
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
We propose a novel adaptive empirical Bayesian (AEB) method for sparse d...
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08/09/2017