Szerző: " Hegedűs István"

Danner Gábor; Hegedűs István; Jelasity Márk: Improving Gossip Learning via Limited Model Merging.
In: Advances in Computational Collective Intelligence : 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings. Springer Nature Switzerland, Cham, pp. 351-363. (2023) ISBN 9783031417733; 9783031417740

Berta Árpád; Danner Gábor; Hegedűs István; Jelasity Márk: Hiding Needles in a Haystack: Towards Constructing Neural Networks that Evade Verification.
In: Proceedings of the 2022 ACM Workshop on Information Hiding and Multimedia Security. Association for Computing Machinery, New York, NY, USA, pp. 51-62. (2022) ISBN 9781450393553

Hegedűs István; Danner Gábor; Jelasity Márk: Decentralized learning works: An empirical comparison of gossip learning and federated learning.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 148. pp. 109-124. ISSN 0743-7315 (2021)

Megyeri István; Hegedűs István; Jelasity Márk: Robust Classification Combined with Robust out-of-Distribution Detection: An Empirical Analysis.
In: 2021 International Joint Conference on Neural Networks (IJCNN). IEEE, Piscataway (NJ), pp. 1-8. (2021) ISBN 9781665439008

Megyeri István; Hegedűs István; Jelasity Márk: Adversarial Robustness of Model Sets.
In: IEEE World Congress on Computational Intelligence (WCCI 2020). IEEE Press, Piscataway (NJ), Azonosító: 9206656-Terjedelem: 8 p. (2020) ISBN 9781728169262

Megyeri István; Hegedűs István; Jelasity Márk: Attacking Model Sets with Adversarial Examples.
In: ESANN 2020 - Proceedings: 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (online event). i6doc.com, Louvain-la-Neuve, pp. 1-6. (2020) ISBN 9782875870735

Hegedűs István; Danner Gábor; Jelasity Márk: Decentralized Recommendation Based on Matrix Factorization: A Comparison of Gossip and Federated Learning.
In: Machine Learning and Knowledge Discovery in Databases: International Workshops of ECML PKDD 2019, Würzburg, Germany, September 16–20, 2019, Proceedings, Part I. Springer International Publishing, Cham (Svájc), pp. 317-332. (2020) ISBN 9783030438234; 9783030438227

Danner Gábor; Hegedűs István; Jelasity Márk: Decentralized machine learning using compressed push-pull averaging.
In: Proceedings of the 1st International Workshop on Distributed Infrastructure for Common Good. Association for Computing Machinery, New York (NY), pp. 31-36. (2020) ISBN 9781450381970

Megyeri István; Hegedűs István; Jelasity Márk: Adversarial robustness of linear models: regularization and dimensionality.
In: ESANN 2019 - Proceedings. i6doc.com, Louvain-la-Neuve, pp. 61-66. (2019) ISBN 9782875870650

Hegedűs István; Danner Gábor; Jelasity Márk: Gossip Learning as a Decentralized Alternative to Federated Learning.
LECTURE NOTES IN COMPUTER SCIENCE, 11534. pp. 74-90. ISSN 0302-9743 (2019)

Danner Gábor; Berta Árpád; Hegedűs István; Jelasity Márk: Robust fully distributed minibatch gradient descent with privacy preservation.
SECURITY AND COMMUNICATION NETWORKS, 2018. Terjedelem: 15 p.-Azonosító: 6728020. ISSN 1939-0114 (2018)

Hegedűs István; Jelasity Márk: Differentially private linear models for gossip learning through data perturbation.
OPEN JOURNAL OF INTERNET OF THINGS, 3 (1). pp. 62-74. ISSN 2364-7108 (2017)

Berta Árpád; Hegedűs István; Jelasity Márk: Dimension Reduction Methods for Collaborative Mobile Gossip Learning.
In: Proceedings of the 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2016). IEEE Computer Society Press, Piscataway, pp. 393-397. (2016) ISBN 978-1-4673-8775-0

Hegedűs István; Jelasity Márk: Distributed Differentially Private Stochastic Gradient Descent: An Empirical Study.
In: Proceedings of the 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2016). IEEE Computer Society Press, Piscataway, pp. 566-573. (2016) ISBN 978-1-4673-8775-0

Hegedűs István; Berta Árpád; Jelasity Márk: Robust Decentralized Differentially Private Stochastic Gradient Descent.
JOURNAL OF WIRELESS MOBILE NETWORKS, UBIQUITOUS COMPUTING, AND DEPENDABLE APPLICATIONS, 7 (2). pp. 20-40. ISSN 2093-5382 (2016)

Hegedűs István; Berta Árpád; Kocsis Levente; Benczúr A. András; Jelasity Márk: Robust Decentralized Low-Rank Matrix Decomposition.
ACM Transactions on Intelligent Systems and Technology, 7 (4). ISSN 2157-6904 (2016)

Hegedűs István; Jelasity Márk; Kocsis Levente; Benczúr András, ifj.: Fully Distributed Robust Singular Value Decomposition.
In: Indranil Gupta, Roger Wattenhofer (szerk.) P2P 2014 : IEEE Fourteenth International Conference on Peer-to-Peer Computing. IEEE Press, Los Alamitos, Azonosító: 6934299-Terjedelem: 9 p.. (2014) ISBN 978-1-4799-6201-3

Berta Árpád; Hegedűs István; Ormándi Róbert: Lightning Fast Asynchronous Distributed K-Means Clustering.
In: European Symposium on Artificial Neural Networks ESANN 2014. UCL, Louvain-la-Neuve, Belgium, pp. 99-104. (2014) ISBN 9782874190957

Ormándi Róbert; Hegedűs István; Jelasity Márk: Gossip learning with linear models on fully distributed data.
Concurrency and Computation: Practice and Experience, 25 (4). pp. 556-571. ISSN 1532-0626 (2013)

Szörényi Balázs; Busa-Fekete Róbert; Hegedűs István; Ormándi Róbert; Jelasity Márk; Kégl Balázs: Gossip-based distributed stochastic bandit algorithms.
In: 30th International Conference on Machine Learning. pp. 1056-1064.

Hegedűs István; Ormándi Róbert; Jelasity Márk: Massively distributed concept drift handling in large networks.
Advances in Complex Systems, 16 (4-5). Terjedelem: 28 p.-Azonosító: 231200. ISSN 0219-5259 (2013)

Hegedűs István; Ormándi Róbert; Jelasity Márk: Gossip-based learning under drifting concepts in fully distributed networks.
In: Proceedings of the 6th IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2012). Lyon, 10-14 September 2012. IEEE Computer Society, Los Alamitos, pp. 79-88. (2012) ISBN 978-0-7695-4851-7

Hegedűs István; Busa-Fekete Róbert; Ormándi Róbert; Jelasity Márk; Kégl Balázs: Peer-to-Peer Multi-Class Boosting.
In: Euro-Par 2012 Parallel Processing : 18th International Conference, Euro-Par 2012, Rhodes Island, Greece, August 27-31, 2012. Proceedings. Springer, pp. 389-400. (2012)

Ormándi Róbert; Hegedűs István; Jelasity Márk: Asynchronous peer-to-peer data mining with stochastic gradient descent.
Lecture Notes in Computer Science, 6852. pp. 528-540. ISSN 0302-9743 (2011)

Farkas Richárd; Berend Gábor; Hegedűs István; Kárpáti András; Krich Balázs: Automatic free-text-tagging of online news archives.
In: Proceedings of the 19th Europen Conference on Artificial Intelligence (ECAI2010). IOS Press, Amsterdam, pp. 529-534. (2010) ISBN 978-1-60750-605-8

Ormándi Róbert; Hegedűs István; Jelasity Márk: Overlay management for fully distributed user-based collaborative filtering.
Lecture Notes in Computer Science, 6271. pp. 446-457. ISSN 0302-9743 (2010)

Ormándi Róbert; Hegedűs István; Csernai Kornél; Jelasity Márk: Towards inferring ratings from user behavior in BitTorrent communities.
In: 19th IEEE International Workshop on Enabling Technologies: Infrastructures for Collaborative Enterprises (WETICE). Larissa, 28-30 June 2010. IEEE Computer Society, Los Alamitos, pp. 217-222. (2010) ISBN 978-1-4244-7216-1