Luigi Nardi

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Kunle OlukotunCadence Design Systems Professor of Computer Science, Stanford UniversityEmail yang diverifikasi di stanford.edu
Paul KellyProfessor of Software Technology, Imperial College LondonEmail yang diverifikasi di imperial.ac.uk
Bruno BodinAssistant Professor, Yale-NUS CollegeEmail yang diverifikasi di acm.org
Andrew DavisonProfessor of Robot Vision, Department of Computing, Imperial College LondonEmail yang diverifikasi di doc.ic.ac.uk
Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyEmail yang diverifikasi di cs.uni-freiburg.de
Michael O'BoyleProfessor of Computer Science, University of EdinburghEmail yang diverifikasi di inf.ed.ac.uk
Artur SouzaPhD Student, UFMGEmail yang diverifikasi di dcc.ufmg.br
Christopher RéComputer Science, Stanford UniversityEmail yang diverifikasi di cs.stanford.edu
Emanuele VespaSoftware Engineer, Computer VisionEmail yang diverifikasi di magicleap.com
Daniel KangUIUCEmail yang diverifikasi di illinois.edu
Peter BailisGoogleEmail yang diverifikasi di google.com
Matei ZahariaUC Berkeley and DatabricksEmail yang diverifikasi di berkeley.edu
Cody ColemanCoactive AIEmail yang diverifikasi di cs.stanford.edu
Andy NisbetResearch Fellow in Low Power Virtualisation for Many Core, APT Group, School of Computer ScienceEmail yang diverifikasi di manchester.ac.uk
John MawerUniversity of ManchesterEmail yang diverifikasi di manchester.ac.uk
Zeeshan ZiaRetrocausal, Inc.Email yang diverifikasi di retrocausal.ai
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchEmail yang diverifikasi di ai.uni-hannover.de
Mikel LujanDepartment of Computer Science, University of ManchesterEmail yang diverifikasi di manchester.ac.uk
Deepak NarayananNVIDIAEmail yang diverifikasi di nvidia.com
Volker KruegerLund UniversityEmail yang diverifikasi di cs.lth.se

Ikuti

Luigi Nardi

Associate Professor in Machine Learning at Lund University

Email yang diverifikasi di cs.lth.se - Beranda

Machine Learning Bayesian Optimization


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Dawnbench: An end-to-end deep learning benchmark and competition C Coleman, D Narayanan, D Kang, T Zhao, J Zhang, L Nardi, P Bailis, ... NIPS ML Systems Workshop 100 (101), 102, 2017	400	2017
Spatial: A language and compiler for application accelerators D Koeplinger, M Feldman, R Prabhakar, Y Zhang, S Hadjis, R Fiszel, ... Proceedings of the 39th ACM SIGPLAN Conference on Programming Language …, 2018	275	2018
Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM L Nardi, B Bodin, MZ Zia, J Mawer, A Nisbet, PHJ Kelly, AJ Davison, ... 2015 IEEE international conference on robotics and automation (ICRA), 5783-5790, 2015	204	2015
Practical design space exploration L Nardi, D Koeplinger, K Olukotun 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation …, 2019	157*	2019
Analysis of dawnbench, a time-to-accuracy machine learning performance benchmark C Coleman, D Kang, D Narayanan, L Nardi, T Zhao, J Zhang, P Bailis, ... ACM SIGOPS Operating Systems Review 53 (1), 14-25, 2019	148	2019
Efficient octree-based volumetric SLAM supporting signed-distance and occupancy mapping E Vespa, N Nikolov, M Grimm, L Nardi, PHJ Kelly, S Leutenegger IEEE Robotics and Automation Letters 3 (2), 1144-1151, 2018	110	2018
Slambench2: Multi-objective head-to-head benchmarking for visual slam B Bodin, H Wagstaff, S Saecdi, L Nardi, E Vespa, J Mawer, A Nisbet, ... 2018 IEEE International Conference on Robotics and Automation (ICRA), 3637-3644, 2018	75	2018
BO: Augmenting acquisition functions with user beliefs for bayesian optimization C Hvarfner, D Stoll, A Souza, M Lindauer, F Hutter, L Nardi International Conference on Learning Representations (ICLR), 2022	73	2022
Integrating algorithmic parameters into benchmarking and design space exploration in 3D scene understanding B Bodin, L Nardi, MZ Zia, H Wagstaff, G Sreekar Shenoy, M Emani, ... International Conference on Parallel Architectures and Compilation (PACT), 57-69, 2016	63	2016
Bayesian optimization with a prior for the optimum A Souza, L Nardi, LB Oliveira, K Olukotun, M Lindauer, F Hutter Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021	62*	2021
Navigating the landscape for real-time localization and mapping for robotics and virtual and augmented reality S Saeedi, B Bodin, H Wagstaff, A Nisbet, L Nardi, J Mawer, N Melot, ... Proceedings of the IEEE 106 (11), 2020-2039, 2018	61	2018
A structure-exploiting numbering algorithm for finite elements on extruded meshes, and its performance evaluation in Firedrake GT Bercea, ATT McRae, DA Ham, L Mitchell, F Rathgeber, L Nardi, ... Geoscientific Model Development 9 (10), 3803-3815, 2016	47*	2016
Joint entropy search for maximally-informed Bayesian optimization C Hvarfner, F Hutter, L Nardi Advances in Neural Information Processing Systems 35, 11494-11506, 2022	41	2022
Comparative Design Space Exploration of Dense and Semi-Dense SLAM MZ Zia, L Nardi, A Jack, E Vespa, B Bodin, PHJ Kelly, AJ Davison International Conference on Robotics and Automation (ICRA), 2016	39	2016
Increasing the scope as you learn: Adaptive bayesian optimization in nested subspaces L Papenmeier, L Nardi, M Poloczek Advances in Neural Information Processing Systems 35, 11586-11601, 2022	38	2022
Application-oriented design space exploration for SLAM algorithms S Saeedi, L Nardi, E Johns, B Bodin, PHJ Kelly, AJ Davison 2017 IEEE International Conference on Robotics and Automation (ICRA), 5716-5723, 2017	38	2017
Skill-based multi-objective reinforcement learning of industrial robot tasks with planning and knowledge integration M Mayr, F Ahmad, K Chatzilygeroudis, L Nardi, V Krueger 2022 IEEE international conference on robotics and biomimetics (ROBIO), 1995 …, 2022	30	2022
Algorithmic performance-accuracy trade-off in 3d vision applications using hypermapper L Nardi, B Bodin, S Saeedi, E Vespa, AJ Davison, PHJ Kelly 2017 IEEE International Parallel and Distributed Processing Symposium …, 2017	29	2017
YAO: a software for variational data assimilation using numerical models L Nardi, C Sorror, F Badran, S Thiria Computational Science and Its Applications–ICCSA 2009: International …, 2009	29	2009
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso L Nardi, A Gramfort, J Salmon, K Sehic 1st International Conference on Automated Machine Learning (AutoML), 2022	28*	2022

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