Tao Luo
Orcid: 0000-0002-2029-0362Affiliations:
- Shanghai Jiao Tong University, China
- Hong Kong University of Science and Technology, Department of Mathematics, Hong Kong (former)
According to our database1,
Tao Luo
authored at least 38 papers
between 2016 and 2024.
Collaborative distances:
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Bibliography
2024
Analyzing and Bridging the Gap between Maximizing Total Reward and Discounted Reward in Deep Reinforcement Learning.
CoRR, 2024
Probing Implicit Bias in Semi-gradient Q-learning: Visualizing the Effective Loss Landscapes via the Fokker-Planck Equation.
CoRR, 2024
Geometry of Critical Sets and Existence of Saddle Branches for Two-layer Neural Networks.
CoRR, 2024
CoRR, 2024
A priori Estimates for Deep Residual Network in Continuous-time Reinforcement Learning.
CoRR, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
Trans. Mach. Learn. Res., 2023
On Residual Minimization for PDEs: Failure of PINN, Modified Equation, and Implicit Bias.
CoRR, 2023
CoRR, 2023
2022
On the Exact Computation of Linear Frequency Principle Dynamics and Its Generalization.
SIAM J. Math. Data Sci., 2022
Nonlinear Weighted Directed Acyclic Graph and A Priori Estimates for Neural Networks.
SIAM J. Math. Data Sci., 2022
A regularised deep matrix factorised model of matrix completion for image restoration.
IET Image Process., 2022
Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks.
CoRR, 2022
An Experimental Comparison Between Temporal Difference and Residual Gradient with Neural Network Approximation.
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
An Upper Limit of Decaying Rate with Respect to Frequency in Linear Frequency Principle Model.
Proceedings of the Mathematical and Scientific Machine Learning, 2022
2021
Finite Temperature Cauchy-Born Rule and Stability of Crystalline Solids with Point Defects.
Multiscale Model. Simul., 2021
Energy Scaling and Asymptotic Properties of One-Dimensional Discrete System with Generalized Lennard-Jones (m, n) Interaction.
J. Nonlinear Sci., 2021
J. Mach. Learn. Res., 2021
Embedding Principle: a hierarchical structure of loss landscape of deep neural networks.
CoRR, 2021
MOD-Net: A Machine Learning Approach via Model-Operator-Data Network for Solving PDEs.
CoRR, 2021
Towards Understanding the Condensation of Two-layer Neural Networks at Initial Training.
CoRR, 2021
CoRR, 2021
Linear Frequency Principle Model to Understand the Absence of Overfitting in Neural Networks.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
Fourier-domain Variational Formulation and Its Well-posedness for Supervised Learning.
CoRR, 2020
A regularized deep matrix factorized model of matrix completion for image restoration.
CoRR, 2020
CoRR, 2020
Proceedings of Mathematical and Scientific Machine Learning, 2020
2019
Explicitizing an Implicit Bias of the Frequency Principle in Two-layer Neural Networks.
CoRR, 2019
CoRR, 2019
2016
Energy Scaling and Asymptotic Properties of Step Bunching in Epitaxial Growth with Elasticity Effects.
Multiscale Model. Simul., 2016