21 citations · 59 across the 12 of their papers we have counts for
5 papers · 1 filter
Structured Logconcave Sampling with a Restricted Gaussian Oracle
Yin Tat Lee, Ruoqi Shen, Kevin Tian
We give algorithms for sampling several structured logconcave families to high accuracy. We further develop a reduction framework, inspired by proximal point methods in convex opti…
Generalized Leverage Score Sampling for Neural Networks
Jason D. Lee, Ruoqi Shen, Zhao Song +2
Leverage score sampling is a powerful technique that originates from theoretical computer science, which can be used to speed up a large number of fundamental questions, e.g. linea…
Composite Logconcave Sampling with a Restricted Gaussian Oracle
Ruoqi Shen, Kevin Tian, Yin Tat Lee
We consider sampling from composite densities on of the form for well-conditioned and convex (but possibly non-smooth) ,…
When is Particle Filtering Efficient for Planning in Partially Observed Linear Dynamical Systems?
Simon S. Du, Wei Hu, Zhiyuan Li +3
Particle filtering is a popular method for inferring latent states in stochastic dynamical systems, whose theoretical properties have been well studied in machine learning and stat…
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
Yin Tat Lee, Ruoqi Shen, Kevin Tian
We show that the gradient norm for , where is strongly convex and smooth, concentrates tightly around its mean. This removes a barrier in…