Vahid Partovi Nia

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Mouloud BelbahriUniversity of MontrealVerified email at umontreal.ca
Masoud AsgharianProfessor, Dept of Math & Stat, McGill UniversityVerified email at mcgill.ca
Bruno AgardÉcole Polytechnique de MontréalVerified email at polymtl.ca
Sajad DarabiUniversiy of California, Los Angeles (UCLA)Verified email at cs.ucla.edu
Anthony DavisonProfessor of Statistics, EPFLVerified email at epfl.ch
Martin Trépanierprofesseur titulaire, Polytechnique Montréal, CIRRELTVerified email at polymtl.ca
Sajjad GhaemiNational Research CouncilVerified email at nrc.ca
Matthieu CourbariauxUniversité de MontréalVerified email at umontreal.ca
Ramchalam Kinattinkara RamakrishnanQualcomm AI Research, TorontoVerified email at mail.mcgill.ca
Yanhui GengHuawei Noah's Ark LabVerified email at huawei.com
Peter GeigenbergerProfessor of Plant Metabolism, Ludwig-Maximilians-Universität MünchenVerified email at bio.lmu.de
Reza DrikvandiAssistant Professor of Statistics, Durham UniversityVerified email at durham.ac.uk
Verbeke GeertKU LeuvenVerified email at med.kuleuven.be
samuel bassettoEcole Polytechnique de Montréal, Grenoble-InPVerified email at polymtl.ca
Manuele Margni(1) CIRAIG, Ecole Polytechnique of Montréal, (2) Haute école d'ingénierie HES-SO ValaisVerified email at polymtl.ca
Olivier Jolliet, 0000-0001-6955-4210Technical University Denmark, DTU-Sustain, Quantitative Sustainability Assessment, Lyngby, DKVerified email at dtu.dk
M. MashinchiShahid Bahonar University of Kerman IranVerified email at uk.ac.ir
Abbas ParchamiDepartment of Statistics, Faculty of Mathematics and Computer Sciences, Shahid Bahonar University ofVerified email at uk.ac.ir
Andrea LodiCornell Tech and Technion -- IITVerified email at cornell.edu
Mostafa Ghannad-RezaieMassachusetts Institute of TechnologyVerified email at umich.edu

Vahid Partovi Nia

Huawei Noah's Ark Lab and Ecole Polytechnique de Montreal

Verified email at polymtl.ca - Homepage

high-dimensional data statistical learning deep learning edge intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Regularized Binary Network Training S Darabi, M Belbahri, M Courbariaux, V Partovi Nia NeurIPS 2019 EMC2 Workshop, 2019	123*	2019
Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy MS Ghaemi, DB DiGiulio, K Contrepois, B Callahan, TTM Ngo, ... Bioinformatics 35 (1), 95-103, 2019	123	2019
Rapid classification of phenotypic mutants of Arabidopsis via metabolite fingerprinting G Messerli, V Partovi Nia, M Trevisan, A Kolbe, N Schauer, ... Plant Physiology 143 (4), 1484-1492, 2007	100	2007
Testing multiple variance components in linear mixed-effects models R Drikvandi, G Verbeke, A Khodadadi, V Partovi Nia Biostatistics 14 (1), 144-159, 2013	70	2013
A visual segmentation method for temporal smart card data MS Ghaemi, B Agard, M Trépanier, V Partovi Nia Transportmetrica A: Transport Science 13 (5), 381-404, 2017	56	2017
How does batch normalization help binary training? E Sari, M Belbahri, VP Nia arXiv preprint arXiv:1909.09139, 2019	34	2019
Assessing public transport travel behaviour from smart card data with advanced data mining techniques B Agard, V Partovi Nia, M Trépanier World Conference on Transport Research 13, 15-18, 2013	34	2013
High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust V Partovi Nia, AC Davison Journal of Statistical Software 47 (ARTICLE), 1-22, 2012	33	2012
Causal inference and mechanism clustering of a mixture of additive noise models S Hu, Z Chen, V Partovi Nia, C Laiwan, Y Geng Advances in Neural Information Processing Systems, 5206-5216, 2018	21	2018
On characterizing full dimensional weak facets in DEA with variable returns to scale technology M Davtalab-Olyaie, I Roshdi, V Partovi Nia, M Asgharian Optimization 64 (11), 2455-2476, 2015	20	2015
Challenges in spatial-temporal data analysis targeting public transport MS Ghaemi, B Agard, V Partovi Nia, M Trépanier IFAC-PapersOnLine 48 (3), 442-447, 2015	20	2015
Impact of occupational exposure to chemicals in life cycle assessment: a novel characterization model based on measured concentrations and labor hours G Kijko, M Margni, V Partovi Nia, G Doudrich, O Jolliet Environmental science & technology 49 (14), 8741-8750, 2015	18	2015
A consistent confidence interval for fuzzy capability index A Parchami, M Mashinchi, V Partovi Nia Applied and Computational Mathematics 7 (ARTICLE), 119-125, 2008	17	2008
Activation adaptation in neural networks F Farhadi, VP Nia, A Lodi arXiv preprint arXiv:1901.09849, 2019	15	2019
Method and system for training binary quantized weight and activation function for deep neural networks LI Xinlin, S Darabi, M Belbahri, VP NIA US Patent App. 16/582,131, 2020	14	2020
Differentiable mask for pruning convolutional and recurrent networks RK Ramakrishnan, E Sari, VP Nia 2020 17th Conference on Computer and Robot Vision (CRV), 222-229, 2020	13	2020
Stochastic ranking and dominance in DEA M Davtalab-Olyaie, M Asgharian, V Partovi Nia International Journal of Production Economics 214, 125-138, 2019	13	2019
Flight deck crew reserve: From data to forecasting AH Homaie-Shandizi, V Partovi Nia, M Gamache, B Agard Engineering Applications of Artificial Intelligence 50, 106-114, 2016	13	2016
Automatic odor prediction for electronic nose M Mirshahi, V Partovi Nia, L Adjengue Journal of Applied Statistics 45 (15), 2788-2799, 2018	11	2018
KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language Models via Knowledge Distillation MS Tahaei, E Charlaix, V Partovi Nia, A Ghodsi, M Rezagholizadeh arXiv preprint arXiv:2109.06243, 2021	9	2021

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