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Shanshan Wu
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A Field Guide to Federated Optimization
J Wang, Z Charles, Z Xu, G Joshi, HB McMahan, B Aguera y Arcas, ...
arXiv preprint arXiv:2107.06917, 2021
3062021
The Sparse Recovery Autoencoder
S Wu, AG Dimakis, S Sanghavi, FX Yu, D Holtmann-Rice, D Storcheus, ...
arXiv preprint arXiv:1806.10175v1, 2018
178*2018
Federated Reconstruction: Partially Local Federated Learning
K Singhal, H Sidahmed, Z Garrett, S Wu, K Rush, S Prakash
Advances in Neural Information Processing Systems (NeurIPS), 2021, 2021
1142021
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
S Wu, AG Dimakis, S Sanghavi, FX Yu, D Holtmann-Rice, D Storcheus, ...
International Conference on Machine Learning (ICML), 2019
622019
Sparse logistic regression learns all discrete pairwise graphical models
S Wu, S Sanghavi, AG Dimakis
Advances in Neural Information Processing Systems (NeurIPS 2019), 2019
602019
Performance Study on a CSMA/CA-Based MAC Protocol for Multi-User MIMO Wireless LANs
S Wu, W Mao, X Wang
IEEE Transactions on Wireless Communications 13 (6), 3153-3166, 2014
462014
Motley: Benchmarking heterogeneity and personalization in federated learning
S Wu, T Li, Z Charles, Y Xiao, Z Liu, Z Xu, V Smith
arXiv preprint arXiv:2206.09262, 2022
342022
Learning Distributions Generated by One-Layer ReLU Networks
S Wu, AG Dimakis, S Sanghavi
Advances in Neural Information Processing Systems (NeurIPS 2019), 2019
272019
Leveraging Sparsity for Efficient Submodular Data Summarization
E Lindgren, S Wu, A Dimakis
Advances in Neural Information Processing Systems (NIPS 2016), 2016
262016
Implicit regularization and convergence for weight normalization
X Wu, E Dobriban, T Ren, S Wu, Z Li, S Gunasekar, R Ward, Q Liu
Advances in Neural Information Processing Systems 33, 2835-2847, 2020
162020
Sparse and Greedy: Sparsifying Submodular Facility Location Problems
E Lindgren, S Wu, A Dimakis
NIPS workshop OPT 2015, 2015
152015
Single Pass PCA of Matrix Products
S Wu, S Bhojanapalli, S Sanghavi, A Dimakis
Advances in Neural Information Processing Systems (NIPS 2016), 2016
92016
Implicit Regularization of Normalization Methods
X Wu, E Dobriban, T Ren, S Wu, Z Li, S Gunasekar, R Ward, Q Liu
arXiv preprint arXiv:1911.07956, 2019
82019
QoS-oriented distributed opportunistic scheduling for wireless networks with hybrid links
W Mao, S Wu, X Wang
IEEE Global Communications Conference (IEEE GLOBECOM 2013), 2013
52013
Performance analysis of random access multi-user MIMO wireless LANs
S Wu, W Mao, X Wang
IEEE Global Communications Conference (IEEE GLOBECOM 2013), 2013
52013
Distributed Opportunistic Scheduling with QoS Constraints for Wireless Networks with Hybrid Links
W Mao, X Wang, S Wu
IEEE Transactions on Vehicular Technology, 2015
32015
Sparse recovery autoencoder
X Yu, S Wu, D Holtmann-rice, D Storcheus, S Kumar, A Rostamizadeh
US Patent App. 16/442,203, 2019
22019
Information-theoretic study on routing path selection in two-way relay networks
S Wu, W Mao, X Wang
Globecom Workshops (GC Wkshps), 2013 IEEE, 2013
12013
Prompt Public Large Language Models to Synthesize Data for Private On-device Applications
S Wu, Z Xu, Y Zhang, Y Zhang, D Ramage
arXiv preprint arXiv:2404.04360, 2024
2024
Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning
L Collins, S Wu, S Oh, KC Sim
NeurIPS Workshop on Federated Learning in the Age of Foundation Models, 2023, 2023
2023
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