Ruoqi Shen
13 papers · 2019–2024 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
π§ Keyword Pioneer π Cross-Pollinator (13) π Conference Polyglot (5) π Academic Marathon (5) π Renaissance Researcher (6)
πΊοΈ
Taxonomy Completionist
(23)
π
Conference Polyglot
(5)
π
Academic Marathon
(5)
π
Century Club
(13)
ποΈ
Keyword Collector
(63)
β
The Questioner
π₯
Unstoppable
(6)
Conferences
COLT (5)
NIPS (5)
ICLR (1)
ICML (1)
UAI (1)
Top co-authors
Keywords
markov chain monte carlo
(6)
mixing time
(5)
hamiltonian monte carlo
(2)
convergence rate
(2)
riemannian hamiltonian monte carlo
(2)
particle filtering
(1)
feature learning
(1)
representation learning
(1)
markov decision process
(1)
regret bound
(1)
value function
(1)
state estimation
(1)
stochastic process
(1)
systems biology
(1)
reinforcement learning
(1)
constrained sampling
(1)
deep learning theory
(1)
markov chain sampling
(1)
data augmentation
(1)
neural tangent kernel
(1)
Papers
How to Fine-Tune Vision Models with SGD
ICLR 2024
Condition-number-independent Convergence Rate of Riemannian Hamiltonian Monte Carlo with Numerical Integrators
COLT 2023
Algorithmic Aspects of the Log-Laplace Transform and a Non-Euclidean Proximal Sampler
COLT 2023
Data Augmentation as Feature Manipulation
ICML 2022
Near-Optimal Randomized Exploration for Tabular Markov Decision Processes
NIPS 2022
Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev
COLT 2022
Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space
NIPS 2022
When is particle filtering efficient for planning in partially observed linear dynamical systems?
UAI 2021
Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions
NIPS 2021
Structured Logconcave Sampling with a Restricted Gaussian Oracle
COLT 2021
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo
COLT 2020
Generalized Leverage Score Sampling for Neural Networks
NIPS 2020
The Randomized Midpoint Method for Log-Concave Sampling
NIPS 2019