2 citations · 4 across the 5 of their papers we have counts for
7 papers
Imaging Anisotropic Conductivities from Current Densities
Huan Liu, Bangti Jin, Xiliang Lu
In this paper, we propose and analyze a reconstruction algorithm for imaging an anisotropic conductivity tensor in a second-order elliptic PDE with a nonzero Dirichlet boundary con…
Generative Learning With Euler Particle Transport
Yuan Gao, Jian Huang, Yuling Jiao +3
We propose an Euler particle transport (EPT) approach for generative learning. The proposed approach is motivated by the problem of finding an optimal transport map from a referenc…
Robust Decoding from Binary Measurements with Cardinality Constraint Least Squares
Zhao Ding, Junjun Huang, Yuling Jiao +2
The main goal of 1-bit compressive sampling is to decode dimensional signals with sparsity level from binary measurements. This is a challenging task due to the presenc…
A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models
Jian Huang, Yuling Jiao, Lican Kang +3
Feature selection is important for modeling high-dimensional data, where the number of variables can be much larger than the sample size. In this paper, we develop a support detect…
A stochastic alternating minimizing method for sparse phase retrieval
Jianfeng Cai, Yuling Jiao, Xiliang Lu +1
Sparse phase retrieval plays an important role in many fields of applied science and thus attracts lots of attention. In this paper, we propose a \underline{sto}chastic alte\underl…
SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties
Jian Huang, Yuling Jiao, Xiliang Lu +2
We propose a semismooth Newton algorithm for pathwise optimization (SNAP) for the LASSO and Enet in sparse, high-dimensional linear regression. SNAP is derived from a suitable form…