Seuraa
Enmao Diao
Enmao Diao
Ph.D., Duke University
Vahvistettu sähköpostiosoite verkkotunnuksessa duke.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
E Diao, J Ding, V Tarokh
2021 International Conference on Learning Representations (ICLR), 2021
3362021
Speech Emotion Recognition with Dual-Sequence LSTM Architecture
J Wang, M Xue, R Culhane, E Diao, J Ding, V Tarokh
2020 IEEE International Conference on Acoustics, Speech and Signal …, 2020
1062020
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training
E Diao, J Ding, V Tarokh
2022 Advances in Neural Information Processing Systems (NeurIPS), 2022
55*2022
Restricted Recurrent Neural Networks
E Diao, J Ding, V Tarokh
2019 IEEE International Conference on Big Data (Big Data), 56-63, 2019
192019
DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression
E Diao, J Ding, V Tarokh
2020 Data Compression Conference (DCC), 3-12, 2020
162020
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations
E Diao, J Ding, V Tarokh
2022 Advances in Neural Information Processing Systems (NeurIPS), 2022
13*2022
Pruning Deep Neural Networks from a Sparsity Perspective
E Diao, G Wang, J Zhang, Y Yang, J Ding, V Tarokh
2023 International Conference on Learning Representations (ICLR), 2023
102023
Dimension Reduced Turbulent Flow Data from Deep Vector Quantizers
M Momenifar, E Diao, V Tarokh, AD Bragg
Journal of Turbulence 23 (4-5), 232-264, 2022
92022
On Statistical Efficiency in Learning
J Ding, E Diao, J Zhou, V Tarokh
IEEE Transactions on Information Theory 67 (4), 2488-2506, 2020
72020
Decentralized Multi-Target Cross-Domain Recommendation for Multi-Organization Collaborations
E Diao, V Tarokh, J Ding
arXiv preprint arXiv:2110.13340, 2021
6*2021
Multimodal Controller for Generative Models
E Diao, J Ding, V Tarokh
2022 Computer Vision and Machine Intelligence (CVMI), 2020
62020
Score-Based Hypothesis Testing for Unnormalized Models
S Wu, E Diao, K Elkhalil, J Ding, V Tarokh
IEEE Access 10, 71936-71950, 2022
42022
A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow
M Momenifar, E Diao, V Tarokh, AD Bragg
2022 Data Compression Conference (DCC), 2022
42022
Quickest Change Detection for Unnormalized Statistical Models
S Wu, E Diao, T Banerjee, J Ding, V Tarokh
arXiv preprint arXiv:2302.00250, 2023
32023
Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models
M Momenifar, E Diao, V Tarokh, AD Bragg
2022 Workshop on AI to Accelerate Science and Engineering (AAAI), 2021
32021
Robust Quickest Change Detection for Unnormalized Models
S Wu, E Diao, J Ding, T Banerjee, V Tarokh
2023 Uncertainty in Artificial Intelligence, 2314-2323, 2023
22023
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders
Q Le, E Diao, X Wang, A Anwar, V Tarokh, J Ding
2022 56th Asilomar Conference on Signals, Systems, and Computers, 1157-1163, 2022
22022
A Penalized Method for the Predictive Limit of Learning
J Ding, E Diao, J Zhou, V Tarokh
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
22018
Once-for-All Federated Learning: Learning From and Deploying to Heterogeneous Clients
K Varma, E Diao, T Roosta, J Ding, T Zhang
2023 International Workshop on Federated Learning for Distributed Data …, 2023
12023
Semi-Supervised Federated Learning for Keyword Spotting
E Diao, EW Tramel, J Ding, T Zhang
arXiv preprint arXiv:2305.05110, 2023
12023
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Artikkelit 1–20