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Lorena Qendro
Lorena Qendro
Nokia Bell Labs, University of Cambridge
Verified email at cam.ac.uk
Title
Cited by
Cited by
Year
Deepx: A software accelerator for low-power deep learning inference on mobile devices
ND Lane, S Bhattacharya, P Georgiev, C Forlivesi, L Jiao, L Qendro, ...
2016 15th ACM/IEEE International Conference on Information Processing in …, 2016
6132016
Deepear: robust smartphone audio sensing in unconstrained acoustic environments using deep learning
ND Lane, P Georgiev, L Qendro
Proceedings of the 2015 ACM international joint conference on pervasive and …, 2015
3952015
ePerceptive: energy reactive embedded intelligence for batteryless sensors
A Montanari, M Sharma, D Jenkus, M Alloulah, L Qendro, F Kawsar
Proceedings of the 18th Conference on Embedded Networked Sensor Systems, 382-394, 2020
312020
Uncertainty-aware covid-19 detection from imbalanced sound data
T Xia, J Han, L Qendro, T Dang, C Mascolo
arXiv preprint arXiv:2104.02005, 2021
262021
Early exit ensembles for uncertainty quantification
L Qendro, A Campbell, P Lio, C Mascolo
Machine Learning for Health, 181-195, 2021
242021
Stochastic-Shield: A probabilistic approach towards training-free adversarial defense in quantized cnns
L Qendro, S Ha, R de Jong, P Maji
Proceedings of the 1st Workshop on Security and Privacy for Mobile AI, 1-6, 2021
82021
Robust and efficient uncertainty aware biosignal classification via early exit ensembles
A Campbell, L Qendro, P Liò, C Mascolo
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
62022
Enhancing the security & privacy of wearable brain-computer interfaces
Z Tarkhani, L Qendro, MOC Brown, O Hill, C Mascolo, A Madhavapeddy
arXiv preprint arXiv:2201.07711, 2022
62022
The benefit of the doubt: Uncertainty aware sensing for edge computing platforms
L Qendro, J Chauhan, AGCP Ramos, C Mascolo
2021 IEEE/ACM Symposium on Edge Computing (SEC), 214-227, 2021
62021
High frequency eeg artifact detection with uncertainty via early exit paradigm
L Qendro, A Campbell, P Liò, C Mascolo
arXiv preprint arXiv:2107.10746, 2021
62021
Mobile health with head-worn devices: Challenges and opportunities
A Ferlini, D Ma, L Qendro, C Mascolo
IEEE Pervasive Computing 21 (3), 52-60, 2022
52022
Practical self-supervised continual learning with continual fine-tuning
CI Tang, L Qendro, D Spathis, F Kawsar, C Mascolo, A Mathur
arXiv preprint arXiv:2303.17235, 2023
32023
Towards adversarial robustness with early exit ensembles
L Qendro, C Mascolo
2022 44th Annual International Conference of the IEEE Engineering in …, 2022
32022
Hybrid-EDL: Improving Evidential Deep Learning for Uncertainty Quantification on Imbalanced Data
T Xia, J Han, L Qendro, T Dang, C Mascolo
Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 2022
22022
Kaizen: Practical Self-Supervised Continual Learning With Continual Fine-Tuning
CI Tang, L Qendro, D Spathis, F Kawsar, C Mascolo, A Mathur
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024
12024
DeepEar
ND Lane, P Georgiev, L Qendro
Proceedings of the 2015 ACM International Joint Conference on Pervasive and …, 2015
12015
UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers
H Jia, YD Kwon, D Ma, N Pham, L Qendro, T Vu, C Mascolo
arXiv preprint arXiv:2402.09264, 2024
2024
Uncertainty-aware Health Diagnostics via Class-balanced Evidential Deep Learning
T Xia, T Dang, J Han, L Qendro, C Mascolo
IEEE Journal of Biomedical and Health Informatics, 2024
2024
Balancing Continual Learning and Fine-tuning for Human Activity Recognition
CI Tang, L Qendro, D Spathis, F Kawsar, A Mathur, C Mascolo
arXiv preprint arXiv:2401.02255, 2024
2024
Uncertainty-Informed On-Device Personalisation Using Early Exit Networks on Sensor Signals
T Fawden, L Qendro, C Mascolo
2023 31st European Signal Processing Conference (EUSIPCO), 1305-1309, 2023
2023
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Articles 1–20