Enmao Diao

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 38

Top Topics

Lossy Image Compression

Vector Quantized

Assisted Learning

Top Venues

IEEE Trans. Inf. Theory

Publications

Enmao Diao, Qi Le, Suya Wu, Xinran Wang, Ali Anwar, Jie Ding, Vahid Tarokh
ColA: Collaborative Adaptation with Gradient Learning. CoRR (2024)
Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
Quickest Change Detection for Unnormalized Statistical Models. IEEE Trans. Inf. Theory 70 (2) (2024)
Yan Zhang, Enmao Diao, Dryver Huston, Tian Xia
A Data-Efficient Deep Learning Method for Rough Surface Clutter Reduction in GPR Images. IEEE Trans. Geosci. Remote. Sens. 62 (2024)
Yuzhe Gu, Enmao Diao
ESC: Efficient Speech Coding with Cross-Scale Residual Vector Quantized Transformers. CoRR (2024)
Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
Score-based Quickest Change Detection for Unnormalized Models. AISTATS (2023)
Enmao Diao, Eric W. Tramel, Jie Ding, Tao Zhang
Semi-Supervised Federated Learning for Keyword Spotting. CoRR (2023)
Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
Pruning Deep Neural Networks from a Sparsity Perspective. CoRR (2023)
Enmao Diao, Ganghua Wang, Jiawei Zhang, Yuhong Yang, Jie Ding, Vahid Tarokh
Pruning Deep Neural Networks from a Sparsity Perspective. ICLR (2023)
Suya Wu, Enmao Diao, Jie Ding, Taposh Banerjee, Vahid Tarokh
Robust Quickest Change Detection for Unnormalized Models. UAI (2023)
Enmao Diao, Eric W. Tramel, Jie Ding, Tao Zhang
Semi-Supervised Federated Learning for Keyword Spotting. ICME Workshops (2023)
Suya Wu, Enmao Diao, Taposh Banerjee, Jie Ding, Vahid Tarokh
Quickest Change Detection for Unnormalized Statistical Models. CoRR (2023)
Enmao Diao, Jie Ding, Vahid Tarokh
Multimodal Controller for Generative Models. CVMI (2022)
Enmao Diao, Jie Ding, Vahid Tarokh
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations. NeurIPS (2022)
Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh, Andrew D. Bragg
A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow. CoRR (2022)
Qi Le, Enmao Diao, Xinran Wang, Ali Anwar, Vahid Tarokh, Jie Ding
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders. IEEECONF (2022)
Suya Wu, Enmao Diao, Khalil Elkhalil, Jie Ding, Vahid Tarokh
Score-Based Hypothesis Testing for Unnormalized Models. IEEE Access 10 (2022)
Qi Le, Enmao Diao, Xinran Wang, Ali Anwar, Vahid Tarokh, Jie Ding
Personalized Federated Recommender Systems with Private and Partially Federated AutoEncoders. CoRR (2022)
Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh, Andrew D. Bragg
A Physics-Informed Vector Quantized Autoencoder for Data Compression of Turbulent Flow. DCC (2022)
Wenjing Yang, Ganghua Wang, Enmao Diao, Vahid Tarokh, Jie Ding, Yuhong Yang
A Theoretical Understanding of Neural Network Compression from Sparse Linear Approximation. CoRR (2022)
Enmao Diao, Jie Ding, Vahid Tarokh
SemiFL: Semi-Supervised Federated Learning for Unlabeled Clients with Alternate Training. NeurIPS (2022)
Enmao Diao, Jie Ding, Vahid Tarokh
Gradient Assisted Learning. CoRR (2021)
Enmao Diao, Jie Ding, Vahid Tarokh
SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients. CoRR (2021)
Enmao Diao, Vahid Tarokh, Jie Ding
Privacy-Preserving Multi-Target Multi-Domain Recommender Systems with Assisted AutoEncoders. CoRR (2021)
Mohammadreza Momenifar, Enmao Diao, Vahid Tarokh, Andrew D. Bragg
Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning Models. CoRR (2021)
Enmao Diao, Jie Ding, Vahid Tarokh
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients. ICLR (2021)
Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
On Statistical Efficiency in Learning. IEEE Trans. Inf. Theory 67 (4) (2021)
Enmao Diao, Jie Ding, Vahid Tarokh
DRASIC: Distributed Recurrent Autoencoder for Scalable Image Compression. DCC (2020)
Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
Deep Clustering of Compressed Variational Embeddings. DCC (2020)
Enmao Diao, Jie Ding, Vahid Tarokh
Multimodal Controller for Generative Models. CoRR (2020)
Jianyou Wang, Michael Xue, Ryan Culhane, Enmao Diao, Jie Ding, Vahid Tarokh
Speech Emotion Recognition with Dual-Sequence LSTM Architecture. ICASSP (2020)
Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
On Statistical Efficiency in Learning. CoRR (2020)
Enmao Diao, Jie Ding, Vahid Tarokh
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients. CoRR (2020)
Enmao Diao, Jie Ding, Vahid Tarokh
Restricted Recurrent Neural Networks. CoRR (2019)
Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
Deep Clustering of Compressed Variational Embeddings. CoRR (2019)
Enmao Diao, Jie Ding, Vahid Tarokh
Distributed Lossy Image Compression with Recurrent Networks. CoRR (2019)
Jianyou Wang, Michael Xue, Ryan Culhane, Enmao Diao, Jie Ding, Vahid Tarokh
Speech Emotion Recognition with Dual-Sequence LSTM Architecture. CoRR (2019)
Enmao Diao, Jie Ding, Vahid Tarokh
Restricted Recurrent Neural Networks. IEEE BigData (2019)
Jie Ding, Enmao Diao, Jiawei Zhou, Vahid Tarokh
A Penalized Method for the Predictive Limit of Learning. ICASSP (2018)