Mingyang Yi

According to our database1, Mingyang Yi authored at least 22 papers between 2019 and 2024.

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

Timeline

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Links

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Bibliography

2024
Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model.
CoRR, 2024

Enhancing Text-to-Image Editing via Hybrid Mask-Informed Fusion.
CoRR, 2024

Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space.
CoRR, 2024

2023
On the Generalization of Diffusion Model.
CoRR, 2023

SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Breaking Correlation Shift via Conditional Invariant Regularizer.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards the Generalization of Contrastive Self-Supervised Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
WER-Net: A New Lightweight Wide-Spectrum Encoding and Reconstruction Neural Network Applied to Computational Spectrum.
Sensors, 2022

Stabilize deep ResNet with a sharp scaling factor τ.
Mach. Learn., 2022

Improved OOD Generalization via Conditional Invariant Regularizer.
CoRR, 2022

Accelerating training of batch normalization: A manifold perspective.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Characterization of Excess Risk for Locally Strongly Convex Population Risk.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Out-of-distribution Generalization with Causal Invariant Transformations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Towards the Generalization of Contrastive Self-Supervised Learning.
CoRR, 2021

Improved OOD Generalization via Adversarial Training and Pre-training.
CoRR, 2021

Towards Accelerating Training of Batch Normalization: A Manifold Perspective.
CoRR, 2021

Improved OOD Generalization via Adversarial Training and Pretraing.
Proceedings of the 38th International Conference on Machine Learning, 2021

Reweighting Augmented Samples by Minimizing the Maximal Expected Loss.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape.
CoRR, 2020

2019
Positively Scale-Invariant Flatness of ReLU Neural Networks.
CoRR, 2019

BN-invariant Sharpness Regularizes the Training Model to Better Generalization.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Improving Deep Learning by Regularized Scale-Free MSE of Representations.
Proceedings of the Neural Information Processing - 26th International Conference, 2019


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