Daniele Bonacorsi

According to our database, Daniele Bonacorsi authored at least 11 papers between 2010 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Improving parametric neural networks for high-energy physics (and beyond).

Luca Anzalone, Tommaso Diotalevi, Daniele Bonacorsi

Mach. Learn. Sci. Technol., September, 2022

Unsupervised Learning and Online Anomaly Detection: An On-Condition Log-Based Maintenance System.

Leticia Decker, Daniel F. Leite, Francesco Minarini, Simone Rossi Tisbeni, Daniele Bonacorsi

Int. J. Embed. Real Time Commun. Syst., 2022

Explainable Log Parsing and Online Interval Granular Classification from Streams of Words.

Leticia Decker, Daniel F. Leite, Daniele Bonacorsi

Proceedings of the IEEE International Conference on Fuzzy Systems, 2022

2021

Preparing Distributed Computing Operations for the HL-LHC Era With Operational Intelligence.

Alessandro Di Girolamo, Federica Legger, Panos Paparrigopoulos, Jaroslava Schovancová, Thomas Beermann, Michael Boehler, Daniele Bonacorsi, Luca Clissa, Leticia Decker de Sousa, Tommaso Diotalevi, Luca Giommi, Maria Grigorieva, Domenico Giordano, David Hohn, Tomas Javurek, Stephane Jezequel, Valentin Kuznetsov, Mario Lassnig, Vasilis Mageirakos, Micol Olocco, Siarhei Padolski, Matteo Paltenghi, Lorenzo Rinaldi, Mayank Sharma, Simone Rossi Tisbeni, Nikodemas Tuckus

Frontiers Big Data, 2021

MLaaS4HEP: Machine Learning as a Service for HEP.

Valentin Kuznetsov, Luca Giommi, Daniele Bonacorsi

Comput. Softw. Big Sci., 2021

Collection and harmonization of system logs and prototypal Analytics services with the Elastic (ELK) suite at the INFN-CNAF computing centre.

Tommaso Diotalevi, Antonio Falabella, Barbara Martelli, Diego Michelotto, Lucia Morganti, Daniele Bonacorsi, Luca Giommi, Simone Rossi Tisbeni

CoRR, 2021

2020

Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach.

Leticia Decker, Daniel F. Leite, Luca Giommi, Daniele Bonacorsi

Proceedings of the 29th IEEE International Conference on Fuzzy Systems, 2020

Comparison of Evolving Granular Classifiers applied to Anomaly Detection for Predictive Maintenance in Computing Centers.

Leticia Decker, Daniel F. Leite, Fabio Viola, Daniele Bonacorsi

Proceedings of the 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2020

2018

Machine learning at the energy and intensity frontiers of particle physics.

Alexander Radovic, Mike Williams, David Rousseau, Michael Kagan, Daniele Bonacorsi, Alexander Himmel, Adam Aurisano, Kazuhiro Terao, Taritree Wongjirad

Nat., 2018

Machine Learning in High Energy Physics Community White Paper.

Kim Albertsson, Piero Altoe, Dustin Anderson, Michael Andrews, Juan Pedro Araque Espinosa, Adam Aurisano, Laurent Basara, Adrian Bevan, Wahid Bhimji, Daniele Bonacorsi, Paolo Calafiura, Mario Campanelli, Louis Capps, Federico Carminati, Stefano Carrazza, Taylor Childers, Elias Coniavitis, Kyle Cranmer, Claire David, Douglas Davis, Javier M. Duarte, Martin Erdmann, Jonas Eschle, Amir Farbin, Matthew Feickert, Nuno Filipe Castro, Conor Fitzpatrick, Michele Floris, Alessandra Forti, Jordi Garra-Tico, Jochen Gemmler, Maria Girone, Paul Glaysher, Sergei Gleyzer, Vladimir V. Gligorov, Tobias Golling, Jonas Graw, Lindsey Gray, Dick Greenwood, Thomas Hacker, John Harvey, Benedikt Hegner, Lukas Heinrich, Ben Hooberman, Johannes Junggeburth, Michael Kagan, Meghan Kane, Konstantin Kanishchev, Przemyslaw Karpinski, Zahari Kassabov, Gaurav Kaul, Dorian Kcira, Thomas Keck, Alexei Klimentov, Jim Kowalkowski, Luke Kreczko, Alexander Kurepin, Rob Kutschke, Valentin Kuznetsov, Nicolas Köhler, Igor Lakomov, Kevin Lannon, Mario Lassnig, Antonio Limosani, Gilles Louppe, Aashrita Mangu, Pere Mato, Narain Meenakshi, Helge Meinhard, Dario Menasce, Lorenzo Moneta, Seth Moortgat, Mark S. Neubauer, Harvey B. Newman, Hans Pabst, Michela Paganini, Manfred Paulini, Gabriel N. Perdue, Uzziel Perez, Attilio Picazio, Jim Pivarski, Harrison Prosper, Fernanda Psihas, Alexander Radovic, Ryan Reece, Aurelius Rinkevicius, Eduardo Rodrigues, Jamal Rorie, David Rousseau, Aaron Sauers, Steven Schramm, Ariel Schwartzman, Horst Severini, Paul Seyfert, Filip Siroky, Konstantin Skazytkin, Mike Sokoloff, Graeme Andrew Stewart, Bob Stienen, Ian Stockdale, Giles Chatham Strong, Savannah Thais, Karen Tomko, Eli Upfal, Emanuele Usai, Andrey Ustyuzhanin, Martin Vala, Sofia Vallecorsa, Mauro Verzetti, Xavier Vilasís-Cardona, Jean-Roch Vlimant, Ilija Vukotic, Sean-Jiun Wang, Gordon Watts, Michael Williams, Wenjing Wu, Stefan Wunsch, Omar Zapata

CoRR, 2018

2010

Distributed Analysis in CMS.

Alessandra Fanfani, M. Anzar Afaq, Jose Afonso Sanches, Julia Andreeva, Giuseppe Bagliesi, Lothar Bauerdick, Stefano Belforte, Patricia Bittencourt Sampaio, Kenneth Bloom, Barry Blumenfeld, Daniele Bonacorsi, Chris Brew, Marco Calloni, Daniele Cesini, Mattia Cinquilli, Giuseppe Codispoti, Jorgen D'Hondt, Liang Dong, Danilo N. Dongiovanni, Giacinto Donvito, David Dykstra, Erik Edelmann, Ricky Egeland, Peter Elmer, Giulio Eulisse, Dave Evans, Federica Fanzago, Fabio Farina, Derek Feichtinger, Ian Fisk, Josep Flix, Claudio Grandi, Yuyi Guo, Kalle Happonen, José M. Hernández, Chih-Hao Huang, Kejing Kang, Edward Karavakis, Matthias Kasemann, Carlos Kavka, Akram Khan, Bockjoo Kim, Jukka Klem, Jesper Koivumäki, Thomas Kress, Peter Kreuzer, Tibor Kurca, Valentin Kuznetsov, Stefano Lacaprara, Kati Lassila-Perini, James Letts, Tomas Lindén, Lee Lueking, Joris Maes, Nicolò Magini, Gerhild Maier, Patricia McBride, Simon Metson, Vincenzo Miccio, Sanjay Padhi, Haifeng Pi, Hassen Riahi, Daniel Riley, Paul Rossman, Pablo Saiz, Andrea Sartirana, Andrea Sciabà, Vijay Sekhri, Daniele Spiga, Lassi A. Tuura, Eric Vaandering, Lukas Vanelderen, Petra Van Mulders, Aresh Vedaee, Ilaria Villella, Eric Wicklund, Tony Wildish, Christoph Wissing, Frank Würthwein

J. Grid Comput., 2010