Browse by UCL people
Group by: Type | Date
Number of items: 6.
Article
Amjad, J;
Lyu, Z;
Rodrigues, MRD;
(2021)
Deep learning model-aware regulatization with applications to Inverse Problems.
IEEE Transactions on Signal Processing
, 69
pp. 6371-6385.
10.1109/TSP.2021.3125601.
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Lyu, Zhaoyan;
Aminian, Gholamali;
Rodrigues, Miguel RD;
(2023)
On Neural Networks Fitting, Compression, and Generalization Behavior via Information-Bottleneck-like Approaches.
Entropy
, 25
(7)
, Article 1063. 10.3390/e25071063.
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Lyu, Zhaoyan;
Miguel R. D., Rodrigues;
(2024)
Exploring the Impact of Additive Shortcuts in Neural Networks via Information Bottleneck-like Dynamics: From ResNet to Transformer.
Entropy
, 26
(11)
, Article 974. 10.3390/e26110974.
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Proceedings paper
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Amjad, Jaweria;
Lyu, Zhaoyan;
Rodrigues, Miguel RD;
(2021)
Regression with Deep Neural Networks: Generalization Error Guarantees, Learning Algorithms, and Regularizers.
In:
2021 29th European Signal Processing Conference (EUSIPCO).
(pp. pp. 1481-1485).
IEEE: Dublin, Ireland.
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Lyu, Zhaoyan;
Aminian, Gholamali;
Rodrigues, Miguel RD;
(2021)
Toward Minimal-Sufficiency in Regression Tasks: An Approach Based on a Variational Estimation Bottleneck.
In:
2021 IEEE 31ST INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP).
IEEE: Gold Coast, Australia.
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Thesis
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Lyu, Zhaoyan;
(2025)
On the Pathway to State-of-the-art Machine Learning Models Generalization: Exploring the Dynamics of Neural Networks Through Information Bottleneck-Inspired Measures.
Doctoral thesis (Ph.D), UCL (University College London).
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