Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Luigi Nardi"'
Publikováno v:
Image Analysis ISBN: 9783031314377
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a539d3291275d02c822b03f49f314940
https://doi.org/10.1007/978-3-031-31438-4_21
https://doi.org/10.1007/978-3-031-31438-4_21
Robot skills systems are meant to reduce robot setup time for new manufacturing tasks. Yet, for dexterous, contact-rich tasks, it is often difficult to find the right skill parameters. One strategy is to learn these parameters by allowing the robot s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bc51bd002e1f0b208f17f93219a46852
http://arxiv.org/abs/2208.01605
http://arxiv.org/abs/2208.01605
Autor:
Adel Ejjeh, Leon Medvinsky, Aaron Councilman, Hemang Nehra, Suraj Sharma, Vikram Adve, Luigi Nardi, Eriko Nurvitadhi, Rob A Rutenbar
Publikováno v:
2022 IEEE 33rd International Conference on Application-specific Systems, Architectures and Processors (ASAP).
Autor:
Jian Zhang, Matei Zaharia, Cody Coleman, Daniel Kang, Christopher Ré, Kunle Olukotun, Luigi Nardi, Deepak Narayanan, Peter Bailis, Tian Zhao
Publikováno v:
ACM SIGOPS Operating Systems Review. 53:14-25
Researchers have proposed hardware, software, and algorithmic optimizations to improve the computational performance of deep learning. While some of these optimizations perform the same operations faster (e.g., increasing GPU clock speed), many other
Reinforcement Learning (RL) is a powerful mathematical framework that allows robots to learn complex skills by trial-and-error. Despite numerous successes in many applications, RL algorithms still require thousands of trials to converge to high-perfo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1cc04e24169396113a8ba23bfde74fe
Autor:
Kunle Olukotun, Marius Lindauer, Luigi Nardi, Leonardo B. Oliveira, Frank Hutter, Artur Souza
Publikováno v:
Machine Learning and Knowledge Discovery in Databases. Research Track ISBN: 9783030865221
ECML/PKDD (3)
ECML/PKDD (3)
While Bayesian Optimization (BO) is a very popular method for optimizing expensive black-box functions, it fails to leverage the experience of domain experts. This causes BO to waste function evaluations on bad design choices (e.g., machine learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad056f1b191089dfc9b6d94806efac01
https://doi.org/10.1007/978-3-030-86523-8_17
https://doi.org/10.1007/978-3-030-86523-8_17
Autor:
Agostino Salerno, Elisa Nardi, Fabio Spaziani, Giovanna Armiento, Marco Proposito, Luigi De Rosa, Maria Rita Montereali, Luigi Nardi, Antonietta Cerbone, F. Zaza, Antonio Salluzzo, Salvatore Chiavarini, Maurizio De Cassan, Massimo Pezza, Raffaela Caprioli, Cinzia Crovato, Juri Rimauro
The purpose of this study is to investigate the current status of contamination due to the heavy metal and organic substances (PAHs, HC >12, organotin compounds, PCB, DDD, DDE, DDT) pollution of the sediments from the coastal area of the Bagnoli brow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9306fa01057487fba5af15f732a4751
Publikováno v:
MASCOTS
Design problems are ubiquitous in scientific and industrial achievements. Scientists design experiments to gain insights into physical and social phenomena, and engineers design machines to execute tasks more efficiently. These design problems are fr
Publikováno v:
ICDCS
Modern real-time business analytic consist of heterogeneous workloads (e.g, database queries, graph processing, and machine learning). These analytic applications need programming environments that can capture all aspects of the constituent workloads
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be1395aa5572e6aeb817a95494af32e7
Autor:
Luigi Nardi, Sajad Saecdi, Harry Wagstaff, Steve Furber, Bruno Bodin, Andrew J. Davison, Michael F. P. O Boyle, Mikel Luján, Emanuele Vespa, John Mawer, Paul H. J. Kelly, Andy Nisbet
Publikováno v:
Bodin, B, Wagstaff, H, Saecdi, S, Nardi, L, Vespa, E, Mawer, J, Nisbet, A, Lujan, M, Furber, S, Davison, A J, Kelly, P H J & O'Boyle, M F P 2018, SLAMBench2 : Multi-Objective Head-to-Head Benchmarking for Visual SLAM . in 2018 IEEE International Conference on Robotics and Automation, ICRA 2018 ., 8460558, IEEE, pp. 3637-3644, 2018 IEEE International Conference on Robotics and Automation, Brisbane, Australia, 21/05/18 . https://doi.org/10.1109/ICRA.2018.8460558
IEEE International Conference on Robotics and Automation (ICRA)
ICRA
Bodin, B, Wagstaff, H, Saeedi, S, Nardi, L, Vespa, E, Mayer, J H, Nisbet, A, Luján, M, Furber, S, Davison, A J, Kelly, P H J & O'Boyle, M 2018, SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM . in The International Conference in Robotics and Automation 2018 . Institute of Electrical and Electronics Engineers (IEEE), Brisbane, QLD, Australia, pp. 3637-3644, 2018 IEEE International Conference on Robotics and Automation, Brisbane, Australia, 21/05/18 . https://doi.org/10.1109/ICRA.2018.8460558
IEEE International Conference on Robotics and Automation (ICRA)
ICRA
Bodin, B, Wagstaff, H, Saeedi, S, Nardi, L, Vespa, E, Mayer, J H, Nisbet, A, Luján, M, Furber, S, Davison, A J, Kelly, P H J & O'Boyle, M 2018, SLAMBench2: Multi-Objective Head-to-Head Benchmarking for Visual SLAM . in The International Conference in Robotics and Automation 2018 . Institute of Electrical and Electronics Engineers (IEEE), Brisbane, QLD, Australia, pp. 3637-3644, 2018 IEEE International Conference on Robotics and Automation, Brisbane, Australia, 21/05/18 . https://doi.org/10.1109/ICRA.2018.8460558
SLAM is becoming a key component of robotics and augmented reality (AR) systems. While a large number of SLAM algorithms have been presented, there has been little effort to unify the interface of such algorithms, or to perform a holistic comparison
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46daaaa45e7cdecc147cef35316a1391
https://doi.org/10.1109/ICRA.2018.8460558
https://doi.org/10.1109/ICRA.2018.8460558