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Bo Li
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On the effectiveness of partial variance reduction in federated learning with heterogeneous data
B Li, MN Schmidt, TS Alstrøm, SU Stich
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
48*2023
Decoupled appearance and motion learning for efficient anomaly detection in surveillance video
B Li, S Leroux, P Simoens
Computer Vision and Image Understanding 210, 103249, 2021
362021
Multi-branch neural networks for video anomaly detection in adverse lighting and weather conditions
S Leroux, B Li, P Simoens
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022
242022
On uncertainty estimation in active learning for image segmentation
B Li, TS Alstrøm
arXiv preprint arXiv:2007.06364, 2020
202020
Raman spectrum matching with contrastive representation learning
B Li, MN Schmidt, TS Alstrøm
Analyst 147 (10), 2238-2246, 2022
182022
Nitroaromatic explosives’ detection and quantification using an attention-based transformer on surface-enhanced Raman spectroscopy maps
B Li, G Zappalá, E Dumont, A Boisen, T Rindzevicius, MN Schmidt, ...
Analyst 148 (19), 4787-4798, 2023
92023
Automated training of location-specific edge models for traffic counting
S Leroux, B Li, P Simoens
Computers and Electrical Engineering 99, 107763, 2022
72022
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity
B Li, Y Esfandiari, MN Schmidt, TS Alstrøm, SU Stich
arXiv preprint arXiv:2306.13263, 2023
42023
Precision and Trust: Algorithms for Substance Identification and Collaborative Learning
B Li
Technical University of Denmark, 2024
2024
An improved analysis of per-sample and per-update clipping in federated learning
B Li, X Jiang, MN Schmidt, TS Alstrøm, SU Stich
The Twelfth International Conference on Learning Representations, 2024
2024
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Articles 1–10