Yuling Jiao

Orcid: 0000-0003-2762-0421

According to our database1, Yuling Jiao authored at least 73 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Deep Ritz Method for Elliptical Multiple Eigenvalue Problems.
J. Sci. Comput., February, 2024

A Stabilized Physics Informed Neural Networks Method for Wave Equations.
CoRR, 2024

Deep Conditional Generative Learning: Model and Error Analysis.
CoRR, 2024

Semi-Supervised Deep Sobolev Regression: Estimation, Variable Selection and Beyond.
CoRR, 2024

Neural Network Approximation for Pessimistic Offline Reinforcement Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Global Optimization via Schrödinger-Föllmer Diffusion.
SIAM J. Control. Optim., October, 2023

Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on Hölder Class.
SIAM J. Math. Anal., August, 2023

Correction to: Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension.
J. Sci. Comput., August, 2023

Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension.
J. Sci. Comput., April, 2023

PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations.
Bioinform., February, 2023

Gaussian Interpolation Flows.
CoRR, 2023

Provable Advantage of Parameterized Quantum Circuit in Function Approximation.
CoRR, 2023

Non-Asymptotic Bounds for Adversarial Excess Risk under Misspecified Models.
CoRR, 2023

Current density impedance imaging with PINNs.
CoRR, 2023

Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression.
CoRR, 2023

GAS: A Gaussian Mixture Distribution-Based Adaptive Sampling Method for PINNs.
CoRR, 2023

Convergence Analysis of the Deep Galerkin Method for Weak Solutions.
CoRR, 2023

Invariant and Sufficient Supervised Representation Learning.
Proceedings of the International Joint Conference on Neural Networks, 2023

Fast Excess Risk Rates via Offset Rademacher Complexity.
Proceedings of the International Conference on Machine Learning, 2023

2022
Sample-Efficient Sparse Phase Retrieval via Stochastic Alternating Minimization.
IEEE Trans. Signal Process., 2022

PSNA: A pathwise semismooth Newton algorithm for sparse recovery with optimal local convergence and oracle properties.
Signal Process., 2022

An Error Analysis of Generative Adversarial Networks for Learning Distributions.
J. Mach. Learn. Res., 2022

GSDAR: a fast Newton algorithm for ℓ <sub>0</sub> regularized generalized linear models with statistical guarantee.
Comput. Stat., 2022

A data-driven line search rule for support recovery in high-dimensional data analysis.
Comput. Stat. Data Anal., 2022

<i>ℓ</i><sub>0</sub>-Regularized high-dimensional accelerated failure time model.
Comput. Stat. Data Anal., 2022

Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks.
CoRR, 2022

Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learning.
CoRR, 2022

Approximation bounds for norm constrained neural networks with applications to regression and GANs.
CoRR, 2022

Approximation with CNNs in Sobolev Space: with Applications to Classification.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Distributed quantile regression for massive heterogeneous data.
Neurocomputing, 2021

Fitting jump additive models.
Comput. Stat. Data Anal., 2021

Wasserstein Generative Learning of Conditional Distribution.
CoRR, 2021

Just Least Squares: Binary Compressive Sampling with Low Generative Intrinsic Dimension.
CoRR, 2021

Analysis of Deep Ritz Methods for Laplace Equations with Dirichlet Boundary Conditions.
CoRR, 2021

Relative Entropy Gradient Sampler for Unnormalized Distributions.
CoRR, 2021

Coordinate Descent for MCP/SCAD Penalized Least Squares Converges Linearly.
CoRR, 2021

Convergence Analysis for the PINNs.
CoRR, 2021

Error Analysis of Deep Ritz Methods for Elliptic Equations.
CoRR, 2021

Convergence Analysis of Schr{ö}dinger-F{ö}llmer Sampler without Convexity.
CoRR, 2021

Non-asymptotic Excess Risk Bounds for Classification with Deep Convolutional Neural Networks.
CoRR, 2021

Convergence Rate Analysis for Deep Ritz Method.
CoRR, 2021

Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality on Hölder Class.
CoRR, 2021

Non-asymptotic Error Bounds for Bidirectional GANs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Generative Learning via Euler Particle Transport.
Proceedings of the Mathematical and Scientific Machine Learning, 2021

Deep Generative Learning via Schrödinger Bridge.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
A Semismooth Newton Algorithm for High-Dimensional Nonconvex Sparse Learning.
IEEE Trans. Neural Networks Learn. Syst., 2020

Generative Learning With Euler Particle Transport.
CoRR, 2020

Deep Dimension Reduction for Supervised Representation Learning.
CoRR, 2020

Robust Decoding from Binary Measurements with Cardinality Constraint Least Squares.
CoRR, 2020

Learning Implicit Generative Models with Theoretical Guarantees.
CoRR, 2020

A Support Detection and Root Finding Approach for Learning High-dimensional Generalized Linear Models.
CoRR, 2020

CoMM-S2: a collaborative mixed model using summary statistics in transcriptome-wide association studies.
Bioinform., 2020

2019
A Nonconvex Model with Minimax Concave Penalty for Image Restoration.
J. Sci. Comput., 2019

Variable Selection via Generalized SELO-Penalized Cox Regression Models.
J. Syst. Sci. Complex., 2019

A stochastic alternating minimizing method for sparse phase retrieval.
CoRR, 2019

Wasserstein-Wasserstein Auto-Encoders.
CoRR, 2019

VIMCO: variational inference for multiple correlated outcomes in genome-wide association studies.
Bioinform., 2019

Deep Generative Learning via Variational Gradient Flow.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Robust Decoding from 1-Bit Compressive Sampling with Ordinary and Regularized Least Squares.
SIAM J. Sci. Comput., 2018

A Constructive Approach to $L_0$ Penalized Regression.
J. Mach. Learn. Res., 2018

SNAP: A semismooth Newton algorithm for pathwise optimization with optimal local convergence rate and oracle properties.
CoRR, 2018

2017
Group Sparse Recovery via the ℓ<sup>0</sup>(ℓ<sup>2</sup>) Penalty: Theory and Algorithm.
IEEE Trans. Signal Process., 2017

Iterative Soft/Hard Thresholding With Homotopy Continuation for Sparse Recovery.
IEEE Signal Process. Lett., 2017

A lower bound based smoothed quasi-Newton algorithm for group bridge penalized regression.
Commun. Stat. Simul. Comput., 2017

2016
Stripe Noise Separation and Removal in Remote Sensing Images by Consideration of the Global Sparsity and Local Variational Properties.
IEEE Trans. Geosci. Remote. Sens., 2016

Alternating Direction Method of Multipliers for Linear Inverse Problems.
SIAM J. Numer. Anal., 2016

An Alternating Direction Method with Continuation for Nonconvex Low Rank Minimization.
J. Sci. Comput., 2016

2015
A multi-parameter regularization model for image restoration.
Signal Process., 2015

Numerical identification of a sparse Robin coefficient.
Adv. Comput. Math., 2015

2014
A Primal Dual Active Set Algorithm With Continuation for Compressed Sensing.
IEEE Trans. Signal Process., 2014

Image Deblurring Via Combined Total Variation and Framelet.
Circuits Syst. Signal Process., 2014

A Primal Dual Active Set with Continuation Algorithm for the \ell^0-Regularized Optimization Problem.
CoRR, 2014

2013
Hybrid regularization image deblurring in the presence of impulsive noise.
J. Vis. Commun. Image Represent., 2013


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