2 citations · 3 across the 12 of their papers we have counts for
13 papers
A Simpler Analysis of the Bansal-Jiang Quasi Monte-Carlo Algorithm via Haar Wavelets
Jiaheng Chen, Agastya Vibhuti Jha, Haotian Jiang
Numerical integration---approximating the integral of a function using point evaluations---is a central task in science and engineering. The two main paradigms for this pro…
Sharp Frobenius-Norm Concentration for Sample Moment Tensors
Jiaheng Chen, Daniel Sanz-Alonso
This paper establishes sharp dimension-free Frobenius-norm concentration inequalities for sample moment tensors. Our bounds are optimal over the sub-Gaussian class, while for Gauss…
Concentration Inequalities for Sample Cross-Covariances
Jiaheng Chen, Daniel Sanz-Alonso
This paper establishes sharp dimension-free concentration and expectation bounds for the deviation of a sample cross-covariance matrix from its mean. For sub-Gaussian random vector…
A Homogeneous Second-Order Descent Ascent Algorithm for Nonconvex-Strongly Concave Minimax Problems
Jia-Hao Chen, Zi Xu, Hui-Ling Zhang
This paper introduces a novel Homogeneous Second-order Descent Ascent (HSDA) algorithm for nonconvex-strongly concave minimax optimization problems. At each iteration, HSDA uniquel…
Convergence Rates for Learning Pseudo-Differential Operators
Jiaheng Chen, Daniel Sanz-Alonso
This paper establishes convergence rates for learning elliptic pseudo-differential operators, a fundamental operator class in partial differential equations and mathematical physic…
High-Dimensional Quasi-Monte Carlo via Combinatorial Discrepancy
Jiaheng Chen, Haotian Jiang, Nathan Kirk
Monte Carlo (MC) and Quasi-Monte Carlo (QMC) methods are classical approaches for the numerical integration of functions over . While QMC methods can achieve faster co…
On the Estimation of Gaussian Moment Tensors
Omar Al-Ghattas, Jiaheng Chen, Daniel Sanz-Alonso
This paper studies two estimators for Gaussian moment tensors: the standard sample moment estimator and a plug-in estimator based on Isserlis's theorem. We establish dimension-free…
Sharp Concentration of Simple Random Tensors II: Asymmetry
Jiaheng Chen, Daniel Sanz-Alonso
This paper establishes sharp concentration inequalities for simple random tensors. Our theory unveils a phenomenon that arises only for asymmetric tensors of order when…
VAMO: Efficient Zeroth-Order Variance Reduction for SGD with Faster Convergence
Jiahe Chen, Ziye Ma
Optimizing large-scale nonconvex problems, common in deep learning, demands balancing rapid convergence with computational efficiency. First-order (FO) optimizers, which serve as t…
Sharp Concentration of Simple Random Tensors
Omar Al-Ghattas, Jiaheng Chen, Daniel Sanz-Alonso
This paper establishes sharp dimension-free concentration inequalities and expectation bounds for the deviation of the sum of simple random tensors from its expectation. As part of…
Precision and Cholesky Factor Estimation for Gaussian Processes
Jiaheng Chen, Daniel Sanz-Alonso
This paper studies the estimation of large precision matrices and Cholesky factors obtained by observing a Gaussian process at many locations. Under general assumptions on the prec…
Optimal Estimation of Structured Covariance Operators
Omar Al-Ghattas, Jiaheng Chen, Daniel Sanz-Alonso +1
This paper establishes optimal convergence rates for estimation of structured covariance operators of Gaussian processes. We study banded operators with kernels that decay rapidly…
Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters
Omar Al-Ghattas, Jiaheng Chen, Daniel Sanz-Alonso +1
This paper investigates covariance operator estimation via thresholding. For Gaussian random fields with approximately sparse covariance operators, we establish non-asymptotic boun…