52 citations · 418 across the 59 of their papers we have counts for
22 papers · 1 filter
Wasserstein Generative Learning of Conditional Distribution
Shiao Liu, Xingyu Zhou, Yuling Jiao +1
Conditional distribution is a fundamental quantity for describing the relationship between a response and a predictor. We propose a Wasserstein generative approach to learning a co…
Sample-Efficient Sparse Phase Retrieval via Stochastic Alternating Minimization
Jian-Feng Cai, Yuling Jiao, Xiliang Lu +1
In this work we propose a nonconvex two-stage \underline{s}tochastic \underline{a}lternating \underline{m}inimizing (SAM) method for sparse phase retrieval. The proposed algorithm…
Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension
Yuling Jiao, Dingwei Li, Min Liu +2
In this paper, we consider recovering dimensional signals from binary measurements corrupted by noises and sign flips under the assumption that the target signals have low…
A Data-Driven Line Search Rule for Support Recovery in High-dimensional Data Analysis
Peili Li, Yuling Jiao, Xiliang Lu +1
In this work, we consider the algorithm to the (nonlinear) regression problems with penalty. The existing algorithms for based optimization problem are often carr…
Analysis of Deep Ritz Methods for Laplace Equations with Dirichlet Boundary Conditions
Chenguang Duan, Yuling Jiao, Yanming Lai +3
Deep Ritz methods (DRM) have been proven numerically to be efficient in solving partial differential equations. In this paper, we present a convergence rate in norm for dee…
Global Optimization via Schr{ö}dinger-F{ö}llmer Diffusion
Yin Dai, Yuling Jiao, Lican Kang +2
We study the problem of finding global minimizers of approximately via sampling from a probability distribution with density $p_σ(x)=…