Fan Chen

activity

20232026

collaborators

11 papers

math.ST2026

Sharp dimensional analysis of midpoint methods for Langevin sampling

Fan Chen, Sinho Chewi, Jianfeng Lu +1

We study deterministic and randomized midpoint discretizations of Langevin dynamics for a target $π \propto e^{- V}$ , where $0 ≺ α I ⪯ \nabla^{2} V ⪯ β I$ and $κ = β / α$ . To achi…

math.ST2026

High-accuracy simulation of Picard HMC, part I: Gaussian cloud correction

Fan Chen, Sinho Chewi, Jianfeng Lu +1

We study the problem of sampling from a continuous density $π \propto exp (- V)$ on $R^{d}$ , where $V \in C^{2} (R^{d})$ has a $β$ -Lipschitz gradient and $π$ satisfies a loga…

cs.LG2026

On the Two Faces of Adam in Separable Linear Classification

Chen Fan, Csaba Szepesvári

We consider the behavior of deterministic, full-batch, bias-corrected Adam in separable linear classification with softmax parametrization under log-loss. In this setting, under a…

math.PR2026

Sharp Gaussian divergence and Bernstein-Markov inequalities

Fan Chen, Sinho Chewi, Jianfeng Lu +1

We prove two dimension-free estimates in Gaussian space. The first is an optimal Meyer-type inequality for the Gaussian divergence: for $p \geq 2$ , \[ \|δV\|_{L^p(γ_d)} \leq \sqrt p\…

math.ST2026

Smoothed Picard Hamiltonian Monte Carlo

Fan Chen, Sinho Chewi, Jianfeng Lu +1

We develop a new low-accuracy sampler, called smoothed Picard Hamiltonian Monte Carlo, which combines Gaussian smoothing, Picard iteration, and higher-order discretization. For a l…

math.ST2026

Accelerated High-Accuracy Sampling from a Warm Start via the Proximal Bouncy Particle Sampler

Fan Chen, Sinho Chewi, Jianfeng Lu +1

We study the problem of sampling from $μ (d x) \propto e^{- V (x)} d x$ on $R^{d}$ , where $V$ is $α$ -strongly convex and $β$ -smooth, and write $κ := β / α$ . We desi…

cs.DS2026

Exact simulation of diffusions and improved algorithms for log-concave sampling

Fan Chen, Sinho Chewi, Alexander Rakhlin +1

We study exact simulation of diffusions via rejection sampling on path space using unbiased estimators of the density ratio obtained from Girsanov's theorem. When applied to the un…

math.ST2026

High-accuracy log-concave sampling with stochastic queries

Fan Chen, Sinho Chewi, Constantinos Daskalakis +1

We show that high-accuracy guarantees for log-concave sampling -- that is, iteration and query complexities which scale as $poly lo g (1/ δ)$ , where $δ$ is the desired target…

cs.LG2026

High-accuracy sampling for diffusion models and log-concave distributions

Fan Chen, Sinho Chewi, Constantinos Daskalakis +1

We present algorithms for diffusion model sampling which obtain $δ$ -error in $polylog (1/ δ)$ steps, given access to $O (δ)$ -accurate score estimates in $L^{2}$ . Thi…

cs.LG2025

DiffEM: Learning from Corrupted Data with Diffusion Models via Expectation Maximization

Danial Hosseintabar, Fan Chen, Giannis Daras +2

Diffusion models have emerged as powerful generative priors for high-dimensional inverse problems, yet learning them when only corrupted or noisy observations are available remains…

cs.LG2023

Fast Convergence of Random Reshuffling under Over-Parameterization and the Polyak-Łojasiewicz Condition

Chen Fan, Christos Thrampoulidis, Mark Schmidt

Modern machine learning models are often over-parameterized and as a result they can interpolate the training data. Under such a scenario, we study the convergence properties of a…