research
∙
09/19/2023
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms
Domain adaptation (DA) is a statistical learning problem that arises whe...
share
research
∙
04/10/2023
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
We analyze the mixing time of Metropolized Hamiltonian Monte Carlo (HMC)...
research
∙
04/08/2023
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry
We study the mixing time of Metropolis-Adjusted Langevin algorithm (MALA...
research
∙
12/01/2022
Hit-and-run mixing via localization schemes
We analyze the hit-and-run algorithm for sampling uniformly from an isot...
research
∙
03/08/2022
Localization Schemes: A Framework for Proving Mixing Bounds for Markov Chains
Two recent and seemingly-unrelated techniques for proving mixing bounds ...
research
∙
09/27/2021
Minimax Mixing Time of the Metropolis-Adjusted Langevin Algorithm for Log-Concave Sampling
We study the mixing time of the Metropolis-adjusted Langevin algorithm (...
research
∙
10/29/2020
Domain adaptation under structural causal models
Domain adaptation (DA) arises as an important problem in statistical mac...
research
∙
05/29/2019
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients
Hamiltonian Monte Carlo (HMC) is a state-of-the-art Markov chain Monte C...
research
∙
11/20/2018
Sampling Can Be Faster Than Optimization
Optimization algorithms and Monte Carlo sampling algorithms have provide...
research
∙
04/04/2018
Stability and Convergence Trade-off of Iterative Optimization Algorithms
The overall performance or expected excess risk of an iterative machine ...
research
∙
01/08/2018
Log-concave sampling: Metropolis-Hastings algorithms are fast!
We consider the problem of sampling from a strongly log-concave density ...
research
∙
10/23/2017
Fast MCMC sampling algorithms on polytopes
We propose and analyze two new MCMC sampling algorithms, the Vaidya walk...
research
∙
12/11/2016
Self-calibrating Neural Networks for Dimensionality Reduction
Recently, a novel family of biologically plausible online algorithms for...
research
∙
05/26/2014
