52 citations · 418 across the 59 of their papers we have counts for
7 papers · 1 filter
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…
Deep Dimension Reduction for Supervised Representation Learning
Jian Huang, Yuling Jiao, Xu Liao +2
The goal of supervised representation learning is to construct effective data representations for prediction. Among all the characteristics of an ideal nonparametric representation…
Learning Implicit Generative Models with Theoretical Guarantees
Yuan Gao, Jian Huang, Yuling Jiao +1
We propose a \textbf{uni}fied \textbf{f}ramework for \textbf{i}mplicit \textbf{ge}nerative \textbf{m}odeling (UnifiGem) with theoretical guarantees by integrating approaches from o…
-Regularized High-dimensional Accelerated Failure Time Model
Xingdong Feng, Jian Huang, Yuling Jiao +1
We develop a constructive approach for -penalized estimation in the sparse accelerated failure time (AFT) model with high-dimensional covariates. Our proposed method is bas…
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…