Zhaoyan Lyu

Gholamali Aminian

Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

2023

On Neural Networks Fitting, Compression, and Generalization Behavior via Information-Bottleneck-like Approaches.

[BibT_eX]

[DOI]

Gholamali Aminian

Entropy, July, 2023

BITS-Net: Blind Image Transparency Separation Network.

[BibT_eX]

[DOI]

Chao Zhou

Proceedings of the IEEE International Conference on Image Processing, 2023

2021

Deep Learning Model-Aware Regulatization With Applications to Inverse Problems.

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2021

Toward Minimal-Sufficiency in Regression Tasks: An Approach Based on a Variational Estimation Bottleneck.

[BibT_eX]

[DOI]

Gholamali Aminian

Proceedings of the 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP), 2021

Regression with Deep Neural Networks: Generalization Error Guarantees, Learning Algorithms, and Regularizers.

[BibT_eX]

[DOI]

Proceedings of the 29th European Signal Processing Conference, 2021

2020

Model-Aware Regularization For Learning Approaches To Inverse Problems.

[BibT_eX]

[DOI]

CoRR, 2020

A Popularity- and Mobility-Aware Multi-layer Caching with Feedback Mechanism for Highway Vehicular Networks.

[BibT_eX]

[DOI]

Proceedings of the 92nd IEEE Vehicular Technology Conference, 2020

2019

Deep Learning for Inverse Problems: Bounds and Regularizers.

[BibT_eX]

[DOI]