
Bayesian Robustness: A Nonasymptotic Viewpoint
We study the problem of robustly estimating the posterior distribution f...
read it

HighOrder Langevin Diffusion Yields an Accelerated MCMC Algorithm
We propose a Markov chain Monte Carlo (MCMC) algorithm based on thirdor...
read it

Efficient and Scalable Bayesian Neural Nets with Rank1 Factors
Bayesian neural networks (BNNs) demonstrate promising success in improvi...
read it

On Thompson Sampling with Langevin Algorithms
Thompson sampling is a methodology for multiarmed bandit problems that ...
read it

Is There an Analog of Nesterov Acceleration for MCMC?
We formulate gradientbased Markov chain Monte Carlo (MCMC) sampling as ...
read it

Estimate exponential memory decay in Hidden Markov Model and its applications
Inference in hidden Markov model has been challenging in terms of scalab...
read it

Stochastic Gradient MCMC Methods for Hidden Markov Models
Stochastic gradient MCMC (SGMCMC) algorithms have proven useful in scal...
read it

A Complete Recipe for Stochastic Gradient MCMC
Many recent Markov chain Monte Carlo (MCMC) samplers leverage continuous...
read it

On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo
We provide convergence guarantees in Wasserstein distance for a variety ...
read it

Deep Mixture of Experts via Shallow Embedding
Larger networks generally have greater representational power at the cos...
read it

Sampling Can Be Faster Than Optimization
Optimization algorithms and Monte Carlo sampling algorithms have provide...
read it

Stochastic Gradient MCMC for State Space Models
State space models (SSMs) are a flexible approach to modeling complex ti...
read it
Yian Ma
is this you? claim profile