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Jie Ding
Jie Ding
Associate Professor, University of Minnesota Twin Cities
Verifierad e-postadress på umn.edu - Startsida
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HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients
E Diao, J Ding, V Tarokh
https://arxiv.org/pdf/2010.01264.pdf, 2020
4022020
Model Selection Techniques -- An Overview
J Ding, V Tarokh, Y Yang
IEEE Signal Processing Magazine, 2018
3172018
Speech emotion recognition with dual-sequence LSTM architecture
J Wang, M Xue, R Culhane, E Diao, J Ding, V Tarokh
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
1302020
Bridging AIC and BIC: a new criterion for autoregression
J Ding, V Tarokh, Y Yang
IEEE Transactions on Information Theory 64 (6), 4024-4043, 2017
892017
Fednas: Federated deep learning via neural architecture search
C He, E Mushtaq, J Ding, S Avestimehr
872021
Perturbation analysis of orthogonal matching pursuit
J Ding, L Chen, Y Gu
IEEE Transactions on Signal processing 61 (2), 398-410, 2012
822012
Perturbation analysis of orthogonal matching pursuit
J Ding, L Chen, Y Gu
IEEE Transactions on Signal processing 61 (2), 398-410, 2012
822012
Assisted Learning: A Framework for Multi-Organization Learning
X Xian, X Wang, J Ding, R Ghanadan
NeurIPS 2020 (spotlight), arXiv preprint arXiv:2004.00566, 2020
472020
Federated learning challenges and opportunities: An outlook
J Ding, E Tramel, AK Sahu, S Wu, S Avestimehr, T Zhang
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
452022
Bayesian model comparison with the Hyvärinen score: Computation and consistency
S Shao, PE Jacob, J Ding, V Tarokh
Journal of the American Statistical Association, 2019
442019
SemiFL: Communication efficient semi-supervised federated learning with unlabeled clients
E Diao, J Ding, V Tarokh
392021
Semifl: Semi-supervised federated learning for unlabeled clients with alternate training
E Diao, J Ding, V Tarokh
Advances in Neural Information Processing Systems 35, 17871-17884, 2022
352022
Information laundering for model privacy
X Wang, Y Xiang, J Gao, J Ding
arXiv preprint arXiv:2009.06112, 2020
302020
Multiple change point analysis: Fast implementation and strong consistency
J Ding, Y Xiang, L Shen, V Tarokh
IEEE Transactions on Signal Processing 65 (17), 4495-4510, 2017
212017
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
182020
Complementary lattice arrays for coded aperture imaging
J Ding, M Noshad, V Tarokh
Journal of the Optical Society of America A 33 (5), 863-881, 2016
162016
Explainable multi-task learning for multi-modality biological data analysis
X Tang, J Zhang, Y He, X Zhang, Z Lin, S Partarrieu, EB Hanna, Z Ren, ...
Nature communications 14 (1), 2546, 2023
152023
SLANTS: Sequential adaptive nonlinear modeling of time series
Q Han, J Ding, EM Airoldi, V Tarokh
IEEE Transactions on Signal Processing 65 (19), 4994-5005, 2017
152017
Robustness of orthogonal matching pursuit for multiple measurement vectors in noisy scenario
J Ding, L Chen, Y Gu
2012 IEEE International Conference on Acoustics, Speech and Signal …, 2012
142012
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Artiklar 1–20