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ORCIDIstván Hegedüs
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2020 – today
- 2023
[j9]Balázs Nagy
, István Hegedüs, Noémi Sándor, Balázs Egedi, Haaris Mehmood, Karthikeyan Saravanan, Gábor Lóki, Ákos Kiss:
Privacy-preserving Federated Learning and its application to natural language processing. Knowl. Based Syst. 268: 110475 (2023)- [c23]Gábor Danner, István Hegedüs, Márk Jelasity:
Improving Gossip Learning via Limited Model Merging. ICCCI (CCIS Volume) 2023: 351-363 - 2022
- [c22]Árpád Berta, Gábor Danner, István Hegedüs, Márk Jelasity:
Hiding Needles in a Haystack: Towards Constructing Neural Networks that Evade Verification. IH&MMSec 2022: 51-62 - 2021
- [j8]István Hegedüs, Gábor Danner, Márk Jelasity:
Decentralized learning works: An empirical comparison of gossip learning and federated learning. J. Parallel Distributed Comput. 148: 109-124 (2021) - [c21]István Megyeri, István Hegedüs, Márk Jelasity:
Robust Classification Combined with Robust out-of-Distribution Detection: An Empirical Analysis. IJCNN 2021: 1-8 - 2020
- [c20]István Megyeri, István Hegedüs, Márk Jelasity:
Attacking Model Sets with Adversarial Examples. ESANN 2020: 1-6 - [c19]István Megyeri, István Hegedüs, Márk Jelasity:
Adversarial Robustness of Model Sets. IJCNN 2020: 1-8 - [c18]Gábor Danner, István Hegedüs, Márk Jelasity:
Decentralized machine learning using compressed push-pull averaging. DICG@Middleware 2020: 31-36
2010 – 2019
- 2019
- [c17]István Hegedüs, Gábor Danner, Márk Jelasity:
Gossip Learning as a Decentralized Alternative to Federated Learning. DAIS 2019: 74-90 - [c16]István Megyeri, István Hegedüs, Márk Jelasity:
Adversarial robustness of linear models: regularization and dimensionality. ESANN 2019 - [c15]István Hegedüs, Gábor Danner, Márk Jelasity:
Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning. PKDD/ECML Workshops (1) 2019: 317-332 - 2018
- [j7]Gábor Danner, Árpád Berta, István Hegedüs, Márk Jelasity:
Robust Fully Distributed Minibatch Gradient Descent with Privacy Preservation. Secur. Commun. Networks 2018: 6728020:1-6728020:15 (2018) - 2017
- [b1]István Hegedüs:
Gossip-Based Machine Learning in Fully Distributed Environments. University of Szeged, Hungary, 2017 - [j6]István Hegedüs, Márk Jelasity:
Differentially Private Linear Models for Gossip Learning through Data Perturbation. Open J. Internet Things 3(1): 62-74 (2017) - 2016
- [j5]István Hegedüs, Árpád Berta, Márk Jelasity:
Robust Decentralized Differentially Private Stochastic Gradient Descent. J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl. 7(2): 20-40 (2016) - [j4]István Hegedüs, Árpád Berta, Levente Kocsis, András A. Benczúr, Márk Jelasity:
Robust Decentralized Low-Rank Matrix Decomposition. ACM Trans. Intell. Syst. Technol. 7(4): 62:1-62:24 (2016) - [c14]Árpád Berta, István Hegedüs, Márk Jelasity:
Dimension Reduction Methods for Collaborative Mobile Gossip Learning. PDP 2016: 393-397 - [c13]István Hegedüs, Márk Jelasity:
Distributed Differentially Private Stochastic Gradient Descent: An Empirical Study. PDP 2016: 566-573 - 2014
- [c12]Árpád Berta, István Hegedüs, Róbert Ormándi:
Lightning fast asynchronous distributed k-means clustering. ESANN 2014 - [c11]István Hegedüs, Márk Jelasity, Levente Kocsis, András A. Benczúr:
Fully distributed robust singular value decomposition. P2P 2014: 1-9 - 2013
- [j3]István Hegedüs, Róbert Ormándi, Márk Jelasity:
Massively Distributed Concept Drift Handling in Large Networks. Adv. Complex Syst. 16(4-5) (2013) - [j2]Róbert Ormándi, István Hegedüs, Márk Jelasity:
Gossip learning with linear models on fully distributed data. Concurr. Comput. Pract. Exp. 25(4): 556-571 (2013) - [c10]Balázs Szörényi, Róbert Busa-Fekete, István Hegedüs, Róbert Ormándi, Márk Jelasity, Balázs Kégl:
Gossip-based distributed stochastic bandit algorithms. ICML (3) 2013: 19-27 - 2012
- [c9]István Hegedüs, Róbert Busa-Fekete, Róbert Ormándi, Márk Jelasity, Balázs Kégl:
Peer-to-Peer Multi-class Boosting. Euro-Par 2012: 389-400 - [c8]István Hegedüs, Róbert Ormándi, Márk Jelasity:
Gossip-Based Learning under Drifting Concepts in Fully Distributed Networks. SASO 2012: 79-88 - [c7]István Hegedüs, Lehel Nyers, Róbert Ormándi:
Detecting concept drift in fully distributed environments. SISY 2012: 183-188 - 2011
- [c6]Róbert Ormándi, István Hegedüs, Márk Jelasity:
Asynchronous Peer-to-Peer Data Mining with Stochastic Gradient Descent. Euro-Par (1) 2011: 528-540 - [i1]Róbert Ormándi, István Hegedüs, Márk Jelasity:
Efficient P2P Ensemble Learning with Linear Models on Fully Distributed Data. CoRR abs/1109.1396 (2011) - 2010
- [c5]István Hegedüs, Róbert Ormándi, Richárd Farkas, Márk Jelasity:
Novel Balanced Feature Representation for Wikipedia Vandalism Detection Task - Lab Report for PAN at CLEF 2010. CLEF (Notebook Papers/LABs/Workshops) 2010 - [c4]Richárd Farkas, Gábor Berend, István Hegedüs, András Kárpáti, Balázs Krich:
Automatic free-text-tagging of online news archives. ECAI 2010: 529-534 - [c3]Róbert Ormándi, István Hegedüs, Márk Jelasity:
Overlay Management for Fully Distributed User-Based Collaborative Filtering. Euro-Par (1) 2010: 446-457 - [c2]Róbert Ormándi, István Hegedüs, Richárd Farkas:
Opinion Mining by Transformation-Based Domain Adaptation. TSD 2010: 157-164 - [c1]Róbert Ormándi, István Hegedüs, Kornel Csernai, Márk Jelasity:
Towards Inferring Ratings from User Behavior in BitTorrent Communities. WETICE 2010: 217-222
2000 – 2009
- 2009
- [j1]Richárd Farkas, György Szarvas, István Hegedüs, Attila Almási, Veronika Vincze, Róbert Ormándi, Róbert Busa-Fekete:
Research Paper: Semi-automated Construction of Decision Rules to Predict Morbidities from Clinical Texts. J. Am. Medical Informatics Assoc. 16(4): 601-605 (2009)
Coauthor Index
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