Enmao Diao

Orcid: 0000-0002-9151-7990

According to our database1, Enmao Diao authored at least 25 papers between 2018 and 2024.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Quickest Change Detection for Unnormalized Statistical Models.
IEEE Trans. Inf. Theory, February, 2024

2023
Efficient and Collaborative Methods for Distributed Machine Learning.
PhD thesis, 2023

Robust Quickest Change Detection for Unnormalized Models.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Semi-Supervised Federated Learning for Keyword Spotting.
Proceedings of the IEEE International Conference on Multimedia and Expo Workshops, 2023

Pruning Deep Neural Networks from a Sparsity Perspective.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Score-based Quickest Change Detection for Unnormalized Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation.
CoRR, 2022

Score-Based Hypothesis Testing for Unnormalized Models.
IEEE Access, 2022

SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow.
Proceedings of the Data Compression Conference, 2022

Multimodal Controller for Generative Models.
Proceedings of the Computer Vision and Machine Intelligence, 2022

Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021
On Statistical Efficiency in Learning.
IEEE Trans. Inf. Theory, 2021

Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models.
CoRR, 2021

Privacy-Preserving Multi-Target Multi-Domain Recommender Systems with Assisted AutoEncoders.
CoRR, 2021

SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients.
CoRR, 2021

Gradient Assisted Learning.
CoRR, 2021

HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Speech Emotion Recognition with Dual-Sequence LSTM Architecture.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Deep Clustering of Compressed Variational Embeddings.
Proceedings of the Data Compression Conference, 2020

DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression.
Proceedings of the Data Compression Conference, 2020

2019
Distributed Lossy Image Compression with Recurrent Networks.
CoRR, 2019

Restricted Recurrent Neural Networks.
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018
A Penalized Method for the Predictive Limit of Learning.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018


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