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2020 – today
- 2024
[j1]Lukas Balles, Prabhu Teja Sivaprasad, Cédric Archambeau:
On the Choice of Learning Rate for Local SGD. Trans. Mach. Learn. Res. 2024 (2024)- [i5]Martin Wistuba, Prabhu Teja Sivaprasad, Lukas Balles, Giovanni Zappella:
Choice of PEFT Technique in Continual Learning: Prompt Tuning is Not All You Need. CoRR abs/2406.03216 (2024) - 2023
- [i4]Evann Courdier, Prabhu Teja Sivaprasad, François Fleuret:
PAUMER: Patch Pausing Transformer for Semantic Segmentation. CoRR abs/2311.00586 (2023) - [i3]Martin Wistuba, Prabhu Teja Sivaprasad, Lukas Balles, Giovanni Zappella:
Continual Learning with Low Rank Adaptation. CoRR abs/2311.17601 (2023) - 2022
- [c3]Evann Courdier, Prabhu Teja Sivaprasad, François Fleuret:
PAUMER: Patch Pausing Transformer for Semantic Segmentation. BMVC 2022: 737 - 2021
- [c2]Prabhu Teja Sivaprasad, François Fleuret:
Uncertainty Reduction for Model Adaptation in Semantic Segmentation. CVPR 2021: 9613-9623 - [i2]Prabhu Teja Sivaprasad, François Fleuret:
Test time Adaptation through Perturbation Robustness. CoRR abs/2110.10232 (2021) - 2020
- [c1]Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret:
Optimizer Benchmarking Needs to Account for Hyperparameter Tuning. ICML 2020: 9036-9045
2010 – 2019
- 2019
- [i1]Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret:
On the Tunability of Optimizers in Deep Learning. CoRR abs/1910.11758 (2019)
Coauthor Index
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