Pedro M Esperança

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Fabio Maria CarlucciMetaVerified email at meta.com
Binxin RuDPhil Student, University of OxfordVerified email at robots.ox.ac.uk
Chris HolmesVerified email at stats.ox.ac.uk
Louis J. M. AslettAssociate Professor, Department of Mathematical Sciences, Durham UniversityVerified email at durham.ac.uk
Thomas ChurcherImperial College LondonVerified email at imperial.ac.uk
Antoine YangGoogle DeepMindVerified email at google.com
Zhenguo LiHuawei Noah's Ark LabVerified email at huawei.com
Andrew BlagboroughUniversity of CambridgeVerified email at cam.ac.uk
Xingchen WanUniversity of Oxford, GoogleVerified email at google.com
Paulo JúlioEconomics and Research Department, Banco de PortugalVerified email at bportugal.pt
Steven McDonaghSenior Lecturer, University of EdinburghVerified email at ed.ac.uk
Tamas MadaraszJPMorgan ChaseVerified email at jpmorgan.com
Sarah ParisotImperial College LondonVerified email at imperial.ac.uk
Thierry lefèvreCNRS researcher, MontpellierVerified email at ird.fr
Jun WangProfessor, Computer Science, University College LondonVerified email at cs.ucl.ac.uk
Hang XuResearcher, Huawei Noah's Ark LabVerified email at huawei.com
Yongxin YangQueen Mary University of LondonVerified email at qmul.ac.uk
Gregor DevineMosquito Control Laboratory, QIMR Berghofer Medical Research InstituteVerified email at qimrberghofer.edu.au
Oselyne OngChildren's Medical Research InstituteVerified email at cmri.org.au
Elise Ai Hwee KhoUniversity of QueenslandVerified email at uq.edu.au

Pedro M Esperança

Machine Learning Engineer (London, UK)

Verified email at huawei.com

Statistics Machine Learning Deep Learning Homomorphic Encryption


Title Sort by citations Sort by year Sort by 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	179	2019
A review of homomorphic encryption and software tools for encrypted statistical machine learning LJM Aslett, PM Esperança, CC Holmes arXiv:1508.06574, 2015	100	2015
Encrypted statistical machine learning: new privacy preserving methods LJM Aslett, PM Esperança, CC Holmes arXiv:1508.06845, 2015	91	2015
Neural Architecture Generator Optimization B Ru, P Esperanca, F Carlucci Neural Information Processing Systems (NeurIPS 2020), 2020	40	2020
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	33	2018
Encrypted accelerated least squares regression P Esperanca, L Aslett, C Holmes Artificial Intelligence and Statistics (AISTATS 2017), 2017	25	2017
MANAS: Multi-agent neural architecture search V Lopes, FM Carlucci, PM Esperança, M Singh, V Gabillon, A Yang, H Xu, ... Machine Learning, 2023, 2023	23	2023
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	17	2022
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	16	2020
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	15	2022
Evaluating the forecast quality of GDP components: An application to G7 P Júlio, P Esperanca GEE papers 47, 2012	15	2012
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	11	2021
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	10	2020
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	7	2022
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	6	2020
Labor adjustment dynamics: An application of system GMM P Esperança GEE Papers 43, 2011	5	2011
Evaluating the forecast quality of GDP components P Júlio, PM Esperança, JC Fonseca GEE Papers 41, 2011	3	2011
AUTOKD: Automatic Knowledge Distillation Into A Student Architecture Family RH Eyono, FM Carlucci, PM Esperança, B Ru, P Torr arXiv:2111.03555, 2021	1	2021
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
Normalization in deep convolutional neural networks X Zhou, J Sun, N Ye, X Lan, Q Luo, P Esperanca, FM Carlucci, Z Chen, ... US Patent App. 18/180,841, 2023		2023

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