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Pedro M Esperança
Pedro M Esperança
Machine Learning Engineer (London, UK)
Verified email at huawei.com
Title
Cited by
Cited by
Year
NAS evaluation is frustratingly hard
A Yang, PM Esperança, FM Carlucci
International Conference on Learning Representations (ICLR 2020), 2019
1912019
A review of homomorphic encryption and software tools for encrypted statistical machine learning
LJM Aslett, PM Esperança, CC Holmes
arXiv:1508.06574, 2015
1052015
Encrypted statistical machine learning: new privacy preserving methods
LJM Aslett, PM Esperança, CC Holmes
arXiv:1508.06845, 2015
932015
Neural Architecture Generator Optimization
B Ru, P Esperanca, F Carlucci
Neural Information Processing Systems (NeurIPS 2020), 2020
432020
Detection of Plasmodium berghei infected Anopheles stephensi using near-infrared spectroscopy
PM Esperança, AM Blagborough, DF Da, FE Dowell, TS Churcher
Parasites & vectors 11, 377, 2018
342018
MANAS: Multi-agent neural architecture search
V Lopes, FM Carlucci, PM Esperança, M Singh, V Gabillon, A Yang, H Xu, ...
Machine Learning, 2023, 2023
25*2023
Encrypted accelerated least squares regression
P Esperanca, L Aslett, C Holmes
Artificial Intelligence and Statistics (AISTATS 2017), 2017
252017
Long-tail Recognition via Compositional Knowledge Transfer
S Parisot, PM Esperanca, S McDonagh, TJ Madarasz, Y Yang, Z Li
Computer Vision and Pattern Recognition (CVPR 2022), 2022
212022
On Redundancy and Diversity in Cell-based Neural Architecture Search
X Wan, B Ru, PM Esperança, Z Li
International Conference on Learning Representations (ICLR 2022), 2022
182022
Ability of near-infrared spectroscopy and chemometrics to predict the age of mosquitoes reared under different conditions
OTW Ong, EA Kho, PM Esperança, C Freebairn, FE Dowell, GJ Devine, ...
Parasites & vectors 13, 160, 2020
182020
Evaluating the forecast quality of GDP components: An application to G7
P Júlio, P Esperanca
GEE papers 47, 2012
162012
Detection of Plasmodium falciparum in laboratory-reared and naturally infected wild mosquitoes using near-infrared spectroscopy
DF Da, R McCabe, BM Somé, PM Esperança, KA Sala, J Blight, ...
Scientific Reports 11 (1), 10289, 2021
122021
Batch Group Normalization
XY Zhou, J Sun, N Ye, X Lan, Q Luo, BL Lai, P Esperanca, GZ Yang, Z Li
arXiv:2012.02782, 2020
112020
Approximate Neural Architecture Search via Operation Distribution Learning
X Wan, B Ru, PM Esparança, FM Carlucci
Winter Conference on Applications of Computer Vision (WACV 2022), 2022
82022
Functional data analysis techniques to improve the generalizability of near-infrared spectral data for monitoring mosquito populations
PM Esperança, DF Da, B Lambert, RK Dabiré, TS Churcher
BioRxiv, 2020
62020
Advances in neural information processing systems
R Ru, P Esperanca, FM Carlucci
Adv. Neural Inf. Process. Syst 33, 12057-12069, 2020
52020
Labor adjustment dynamics: An application of system GMM
P Esperança
GEE Papers 43, 2011
52011
Evaluating the forecast quality of GDP components
P Júlio, PM Esperança, JC Fonseca
GEE Papers 41, 2011
32011
AUTOKD: Automatic Knowledge Distillation Into A Student Architecture Family
RH Eyono, FM Carlucci, PM Esperança, B Ru, P Torr
arXiv:2111.03555, 2021
12021
Large model emulation by knowledge distillation based nas
FM Carlucci, T Philip, R Eyono, PM Esperanca, RU Binxin
US Patent App. 18/193,815, 2023
2023
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