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ORCIDNatalie Lang
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2020 – today
- 2024
[c4]Natalie Lang, Itamar Assaf, Omer Bokobza, Nir Shlezinger:
Data-Driven Lattices for Vector Quantization. ICASSP 2024: 8080-8084- [i4]Natalie Lang, Alejandro Cohen, Nir Shlezinger:
Stragglers-Aware Low-Latency Synchronous Federated Learning via Layer-Wise Model Updates. CoRR abs/2403.18375 (2024) - 2023
- [j1]Natalie Lang
, Elad Sofer, Tomer Shaked, Nir Shlezinger:
Joint Privacy Enhancement and Quantization in Federated Learning. IEEE Trans. Signal Process. 71: 295-310 (2023) - [c3]Natalie Lang, Elad Sofer, Nir Shlezinger, Rafael G. L. D'Oliveira, Salim El Rouayheb:
CPA: Compressed Private Aggregation for Scalable Federated Learning Over Massive Networks. ICASSP 2023: 1-5 - [i3]Natalie Lang, Nir Shlezinger, Rafael G. L. D'Oliveira, Salim El Rouayheb:
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks. CoRR abs/2308.00540 (2023) - 2022
- [c2]Natalie Lang, Nir Shlezinger:
Joint Privacy Enhancement and Quantization in Federated Learning. ISIT 2022: 2040-2045 - [i2]Natalie Lang, Elad Sofer, Tomer Shaked, Nir Shlezinger:
Joint Privacy Enhancement and Quantization in Federated Learning. CoRR abs/2208.10888 (2022) - 2021
- [c1]Natalie Lang, Joseph M. Francos:
DeepUME: Learning the Universal Manifold Embedding for Robust Point Cloud Registration. BMVC 2021: 397 - [i1]Natalie Lang, Joseph M. Francos:
DeepUME: Learning the Universal Manifold Embedding for Robust Point Cloud Registration. CoRR abs/2112.09938 (2021)
Coauthor Index
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