István Hegedűs
Cited by
Cited by
Gossip learning with linear models on fully distributed data
R Ormándi, I Hegedűs, M Jelasity
Concurrency and Computation: Practice and Experience 25 (4), 556-571, 2013
Gossip learning as a decentralized alternative to federated learning
I Hegedűs, G Danner, M Jelasity
Distributed Applications and Interoperable Systems: 19th IFIP WG 6.1 …, 2019
Decentralized learning works: An empirical comparison of gossip learning and federated learning
I Hegedűs, G Danner, M Jelasity
Journal of Parallel and Distributed Computing 148, 109-124, 2021
Gossip-based distributed stochastic bandit algorithms
B Szorenyi, R Busa-Fekete, I Hegedus, R Ormándi, M Jelasity, B Kégl
International conference on machine learning, 19-27, 2013
Decentralized recommendation based on matrix factorization: A comparison of gossip and federated learning
I Hegedűs, G Danner, M Jelasity
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019
Robust decentralized low-rank matrix decomposition
I Hegedűs, Á Berta, L Kocsis, AA Benczúr, M Jelasity
ACM Transactions on Intelligent Systems and Technology (TIST) 7 (4), 1-24, 2016
Semi-automated construction of decision rules to predict morbidities from clinical texts
R Farkas, G Szarvas, I Hegedűs, A Almási, V Vincze, R Ormándi, ...
Journal of the American Medical Informatics Association 16 (4), 601-605, 2009
Asynchronous peer-to-peer data mining with stochastic gradient descent
R Ormándi, I Hegedűs, M Jelasity
European Conference on Parallel Processing, 528-540, 2011
Overlay management for fully distributed user-based collaborative filtering
R Ormándi, I Hegedűs, M Jelasity
European Conference on Parallel Processing, 446-457, 2010
Robust fully distributed minibatch gradient descent with privacy preservation
G Danner, Á Berta, I Hegedűs, M Jelasity
Security and Communication Networks 2018 (1), 6728020, 2018
Fully distributed robust singular value decomposition
I Hegedűs, M Jelasity, L Kocsis, AA Benczúr
14-th IEEE International Conference on Peer-to-Peer Computing, 1-9, 2014
Privacy-preserving Federated Learning and its application to natural language processing
B Nagy, I Hegedűs, N Sándor, B Egedi, H Mehmood, K Saravanan, G Lóki, ...
Knowledge-Based Systems 268, 110475, 2023
Distributed differentially private stochastic gradient descent: An empirical study
I Hegedus, M Jelasity
2016 24th Euromicro international conference on parallel, distributed, and …, 2016
Gossip-based learning under drifting concepts in fully distributed networks
I Hegedus, R Ormándi, M Jelasity
2012 IEEE Sixth International Conference on Self-Adaptive and Self …, 2012
Automatic free-text-tagging of online news archives
R Farkas, G Berend, I Hegedűs, A Kárpáti, B Krich
ECAI 2010, 529-534, 2010
Detecting concept drift in fully distributed environments
I Hegedűs, L Nyers, R Ormándi
2012 IEEE 10th Jubilee International Symposium on Intelligent Systems and …, 2012
Towards inferring ratings from user behavior in BitTorrent communities
R Ormándi, I Hegedus, K Csernai, M Jelasity
2010 19th IEEE International Workshops on Enabling Technologies …, 2010
Robust decentralized differentially private stochastic gradient descent
I Hegedűs, Á Berta, M Jelasity
Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable …, 2016
Massively distributed concept drift handling in large networks
I Hegedűs, R Ormándi, M Jelasity
Advances in Complex Systems 16 (04n05), 1350021, 2013
Dimension reduction methods for collaborative mobile gossip learning
Á Berta, I Hegedus, M Jelasity
2016 24th Euromicro International Conference on Parallel, Distributed, and …, 2016
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