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Publikationer av Sarunas Girdzijauskas

Refereegranskade

Artiklar

[1]
D. Roy, V. Komini och S. Girdzijauskas, "Classifying falls using out-of-distribution detection in human activity recognition," AI Communications, vol. 36, no. 4, s. 251-267, 2023.
[3]
S. Zamboni et al., "Pedestrian trajectory prediction with convolutional neural networks," Pattern Recognition, vol. 121, 2022.
[4]
D. Roy, S. Girdzijauskas och S. Socolovschi, "Confidence-Calibrated Human Activity Recognition," Sensors, vol. 21, no. 19, s. 6566-6566, 2021.
[5]
S. Antaris, D. Rafailidis och S. Girdzijauskas, "Knowledge distillation on neural networks for evolving graphs," Social Network Analysis and Mining, vol. 11, no. 1, 2021.
[6]
S. Pozzoli et al., "Domain expertise–agnostic feature selection for the analysis of breast cancer data," Artificial Intelligence in Medicine, vol. 108, 2020.
[7]
N. Apolonia et al., "Socially aware microcloud service overlay optimization in community networks," Software, practice & experience, vol. 49, no. 1, 2019.
[8]
A. Soliman et al., "CADIVa : Cooperative and Adaptive Decentralized Identity Validation Model for Social Networks," Social Network Analysis and Mining, vol. 6, no. 1, 2016.
[9]
F. Rahimian et al., "A Distributed Algorithm for Large-Scale Graph Partitioning," ACM Transactions on Autonomous and Adaptive Systems, vol. 10, no. 2, 2015.
[10]
S. Girdzijauskas et al., "Fuzzynet : Ringless Routing in a Ring-like Structured Overlay," Peer-to-Peer Networking and Applications, vol. 4, no. 3, s. 259-273, 2010.
[11]
S. Girdzijauskas, A. Datta och K. Aberer, "Structured Overlay For Heterogeneous Environments : Design and Evaluation of Oscar," ACM Transactions on Autonomous and Adaptive Systems (TAAS), vol. 5, no. 1, 2010.

Konferensbidrag

[12]
M. Isaksson et al., "Adaptive Expert Models for Federated Learning," i Trustworthy Federated Learning : First International Workshop, FL 2022, 2023, s. 1-16.
[13]
A. Samy, Z. T. Kefato och S. Girdzijauskas, "Data-Driven Self-Supervised Graph Representation Learning," i ECAI 2023 : 26th European Conference on Artificial Intelligence, including 12th Conference on Prestigious Applications of Intelligent Systems, PAIS 2023 - Proceedings, 2023, s. 629-636.
[14]
E. Listo Zec et al., "Decentralized Adaptive Clustering of Deep Nets is Beneficial for Client Collaboration," i FL 2022 : Trustworthy Federated Learning, 2023, s. 59-71.
[15]
M. Bonvalet, Z. T. Kefato och S. Girdzijauskas, "Graph2Feat : Inductive Link Prediction via Knowledge Distillation," i ACM Web Conference 2023 : Companion of the World Wide Web Conference, WWW 2023, 2023, s. 805-812.
[16]
Y. Jin et al., "Learning Cellular Coverage from Real Network Configurations using GNNs," i 2023 IEEE 97th Vehicular Technology Conference, VTC 2023-Spring - Proceedings, 2023.
[17]
A. E. Samy och S. Girdzijauskas, "Mitigating Sybil Attacks in Federated Learning," i INFORMATION SECURITY PRACTICE AND EXPERIENCE, ISPEC 2023, 2023, s. 36-51.
[18]
S. Pozzoli och S. Girdzijauskas, "On Learning Embeddings at the Intersection of Communities and Roles," i Proceedings - 2023 10th International Conference on Social Networks Analysis, Management and Security, SNAMS 2023, 2023.
[19]
D. Roy et al., "Private, Fair and Secure Collaborative Learning Framework for Human Activity Recognition," i UbiComp/ISWC '23 Adjunct : Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing, 2023, s. 352-358.
[20]
D. Roy och S. Girdzijauskas, "Temporal Differential Privacy for Human Activity Recognition," i 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), Thessaloniki, Greece, 9 - 13 October 2023, 2023, s. 1-10.
[21]
L. Giaretta et al., "Towards a Realistic Decentralized Naive Bayes with Differential Privacy," i E-Business and Telecommunications - 19th International Conference, ICSBT 2022, and 19th International Conference, SECRYPT 2022, Revised Selected Papers, 2023, s. 98-121.
[22]
M. Isaksson et al., "Adaptive Expert Models for Personalization in Federated Learning," i International Workshop on Trustworthy Federated Learningin Conjunction with IJCAI 2022 (FL-IJCAI'22), 2022.
[23]
F. Cornell et al., "Challenging the Assumption of Structure-based embeddings in Few- and Zero-shot Knowledge Graph Completion," i LREC 2022 : Thirteen International Conference On Language Resources And Evaluation, 2022, s. 6300-6309.
[24]
A. Stefanoni et al., "Detecting Security Patches in Java Projects Using NLP Technology," i ICNLSP 2022 : Proceedings of the 5th International Conference on Natural Language and Speech Processing, 2022, s. 50-56.
[25]
T. Marchioro et al., "Federated Naive Bayes under Differential Privacy," i Proceedings of the 19th International Conference on Security and Cryptography - SECRYPT, 2022, s. 170-180.
[26]
D. Roy och S. Girdzijauskas, "Mixing temporal experts for Human Activity Recognition," i 34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022, 2022, s. 11-18.
[27]
S. Pozzoli och S. Girdzijauskas, "Not Only Degree Matters : Diffusion-Driven Role Recognition," i Proceedings of the 2022 Workshop on Open Challenges in Online Social Networks, OASIS 2022 - Held in conjunction with the 33rd ACM Conference on Hypertext and Social Media, HT 2022, 2022, s. 16-24.
[28]
Y. Jin et al., "Open World Learning Graph Convolution for Latency Estimation in Routing Networks," i 2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2022.
[29]
D. Roy, V. Komini och S. Girdzijauskas, "Out-of-distribution in Human Activity Recognition," i 34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022, 2022, s. 1-10.
[30]
A. Samy et al., "SchemaWalk : Schema Aware Random Walks for Heterogeneous Graph Embedding," i WWW 2022 - Companion Proceedings of the Web Conference 2022, 2022, s. 1157-1166.
[31]
F. Cornell et al., "Symbolic Hyperdimensional Vectors with Sparse Graph Convolutional Neural Networks," i 2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2022.
[32]
L. Giaretta et al., "Towards a Decentralized Infrastructure for Data Marketplaces : Narrowing the Gap between Academia and Industry," i DE 2022 : Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022, 2022, s. 49-56.
[33]
L. Giaretta et al., "Towards a decentralized infrastructure for data marketplaces: narrowing the gap between academia and industry," i DE '22: Proceedings of the 1st International Workshop on Data Economy, 2022, s. 49-56.
[34]
S. Antaris, D. Rafailidis och S. Girdzijauskas, "A Deep Graph Reinforcement Learning Model for Improving User Experience in Live Video Streaming," i 2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2021, s. 1787-1796.
[35]
A. A. Alkathiri et al., "Decentralized Word2Vec Using Gossip Learning," i Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021), 2021.
[36]
Z. T. Kefato et al., "Dynamic embeddings for interaction prediction," i The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021, 2021, s. 1609-1618.
[37]
L. Giaretta et al., "LiMNet : Early-Stage Detection of IoT Botnets with Lightweight Memory Networks," i Computer Security – ESORICS 2021 : 26th European Symposium on Research in Computer Security, Darmstadt, Germany, October 4–8, 2021, Proceedings, Part I, 2021.
[38]
S. Antaris, D. Rafailidis och S. Girdzijauskas, "Meta-reinforcement learning via buffering graph signatures for live video streaming events," i Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2021, 2021, s. 385-392.
[39]
L. Giaretta et al., "PDS2 : A user-centered decentralized marketplace for privacy preserving data processing," i 2021 IEEE 37TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOPS (ICDEW 2021), 2021, s. 92-99.
[40]
L. Giaretta et al., "PDS2: A user-centered decentralized marketplace for privacy preserving data processing," i Third International Workshop on Blockchain and Data Management (BlockDM 2021), in conjunction with the 37th IEEE International Conference on Data Engineering (ICDE), April 19, 2021, Chania, Crete, Greece, 2021.
[41]
Z. T. Kefato och S. Girdzijauskas, "Self-supervised Graph Neural Networks without explicit negative sampling," i The International Workshop on Self-Supervised Learning for the Web (SSL'21), at WWW'21, 2021.
[42]
Z. Lee, S. Girdzijauskas och P. Papapetrou, "Z-Embedding : A Spectral Representation of Event Intervals for Efficient Clustering and Classification," i Machine Learning And Knowledge Discovery In Databases, ECML PKDD 2020, Pt I, 2021, s. 710-726.
[43]
A. Soliman et al., "Decentralized and Adaptive K-Means Clusteringfor Non-IID Data using HyperLogLog Counters," i Proceedings of The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Singapore, 11-16 May 2020., 2020.
[44]
S. Antaris, D. Rafailidis och S. Girdzijauskas, "EGAD : Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming Events," i 2020 IEEE international conference on big data (big data), 2020, s. 1455-1464.
[45]
Z. T. Kefato och S. Girdzijauskas, "Gossip and Attend: Context-Sensitive Graph Representation Learning," i In Proc. of the 14-th International AAAI Conference on Web and Social Media, ICWSM'20, 2020.
[46]
D. Montesi, S. Girdzijauskas och V. Vlassov, "Repeating Link Prediction over Dynamic Graphs," i 2020 IEEE International Conference on Big Data (Big Data), 2020, s. 4420-4428.
[47]
L. Bahri och S. Girdzijauskas, "Blockchain technology : Practical P2P computing (Tutorial)," i Proceedings - 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems, FAS*W 2019, 2019, s. 249-250.
[48]
L. Giaretta och S. Girdzijauskas, "Gossip Learning : Off the Beaten Path," i 2019 IEEE International Conference on Big Data (IEEE Big Data 2019), December 9-12, 2019, Los Angeles, CA, USA, 2019.
[49]
L. Bahri och S. Girdzijauskas, "Trust Mends Blockchains: Living up to Expectations," i IEEE 39th International Conference on Distributed Computing Systems (ICDCS), Dallas, July 7-10 2019, 2019.
[50]
L. Bahri och S. Girdzijauskas, "Trust mends blockchains : Living up to expectations," i Proceedings - International Conference on Distributed Computing Systems, 2019, s. 1358-1368.
[51]
S. Girdzijauskas, G. Pallis och Y. Wu, "Welcome from the Program Chairs," i Proceedings - 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2019, 2019, s. XVI-XVII.
[52]
C. Chen, Y. Tock och S. Girdzijauskas, "BeaConvey: Co-Design of Overlay and Routing for Topic-basedPublish/Subscribe on Small-World Networks," i 12th International Conference on Distributed and Event-Based Systems (DEBS 2018), 2018.
[53]
Z. T. Kefato et al., "CAS2VEC : Network-Agnostic Cascade Prediction in Online Social Networks," i 2018 FIFTH INTERNATIONAL CONFERENCE ON SOCIAL NETWORKS ANALYSIS, MANAGEMENT AND SECURITY (SNAMS), 2018, s. 72-79.
[54]
Z. Kefato et al., "CaTS: Network-Agnostic Virality Prediction Model to Aid Rumour Detection," i International Workshop on Rumours and Deception in Social Media (RDSM 2018), 2018.
[55]
K. Sozinov, V. Vlassov och S. Girdzijauskas, "Human Activity Recognition Using Federated Learning," i 2018 IEEE INT CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, UBIQUITOUS COMPUTING & COMMUNICATIONS, BIG DATA & CLOUD COMPUTING, SOCIAL COMPUTING & NETWORKING, SUSTAINABLE COMPUTING & COMMUNICATIONS, 2018, s. 1103-1111.
[56]
N. Apolonia et al., "SELECT : A distributed publish/subscribe notification system for online social networks," i Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018, 2018, s. 970-979.
[57]
Z. Abbas et al., "Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks," i 2018 IEEE International Congress on Big Data (BigData Congress), 2018, s. 57-65.
[58]
K. Ghoorchian och S. Girdzijauskas, "Spatio-Temporal Multiple Geo-Location Identification on Twitter," i Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, 2018, s. 3412-3421.
[59]
A. Soliman, F. Rahimian och S. Girdzijauskas, "Stad: Stateful Diffusion for Linear Time Community Detection," i 38th IEEE International Conference on Distributed Computing Systems, 2018.
[60]
L. Bahri och S. Girdzijauskas, "When Trust Saves Energy - A Reference Framework for Proof-of-Trust (PoT) Blockchains," i WWW '18 Companion Proceedings of the The Web Conference 2018, 2018, s. 1165-1169.
[61]
A. Soliman och S. Girdzijauskas, "Adagraph : Adaptive graph-based algorithms for spam detection in social networks," i 5th International Conference on Networked Systems, NETYS 2017, 2017, s. 338-354.
[62]
K. Ghoorchian, S. Girdzijauskas och F. Rahimian, "DeGPar : Large Scale Topic Detection usingNode-Cut Partitioning on Dense Weighted Graphs," i 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), 2017, s. 775-785.
[63]
M. A. U. Nasir et al., "Fully dynamic algorithm for top-k densest subgraphs," i CIKM '17 Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017, s. 1817-1826.
[64]
N. Apolonia et al., "Gossip-based service monitoring platform for wireless edge cloud computing," i Proceedings IEEE 14th International Conference on Networking, Sensing and Control (ICNSC), 2017.
[65]
A. Guerrieri et al., "Tovel : Distributed Graph Clustering for Word Sense Disambiguation," i IEEE International Conference on Data Mining Workshops, ICDMW, 2017, s. 623-630.
[66]
L. Bahri et al., "Beat the DIVa : Decentralized Identity Validation for Online Social Networks," i 2016 32ND IEEE INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2016, s. 1330-1333.
[67]
A. Soliman och S. Girdzijauskas, "DLSAS: Distributed Large-Scale Anti-Spam Framework for Decentralized Online Social Networks," i 2016 IEEE 2ND INTERNATIONAL CONFERENCE ON COLLABORATION AND INTERNET COMPUTING (IEEE CIC), 2016, s. 363-372.
[68]
N. Laleh et al., "Gossip-based behavioral group identification in decentralized OSNs," i 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, 2016, s. 676-691.
[69]
A. Soliman et al., "DIVa : Decentralized Identity Validation for Social Networks," i PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015), 2015, s. 383-391.
[70]
M. Sedaghat et al., "Divide the task, multiply the outcome : Cooperative VM consolidation," i Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, 2015, s. 300-305.
[71]
K. Ghoorchian, F. Rahimian och S. Girdzijauskas, "Semi-Supervised Multiple Disambiguation," i IEEE Computer Society Conference Publishing Services, 2015.
[72]
M. A. U. Nasir och S. Girdzijauskas, "Socially-aware distributed hash tables for decentralized online social networks," i Peer-to-Peer Computing (P2P), 2015 IEEE International Conference on, 2015, s. 1-10.
[73]
F. Rahimian et al., "Distributed Vertex-Cut Partitioning," i In the 14th IFIP international conference on Distributed Applications and Interoperable Systems (DAIS’14)., 2014, s. 186-200.
[74]
M. A. U. Nasir, F. Rahimian och S. Girdzijauskas, "Gossip-based partitioning and replication for Online Social Networks," i ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2014, s. 33-42.
[75]
F. Rahimian, S. Girdzijauskas och S. Haridi, "Parallel Community Detection For Cross-Document Coreference," i 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014; University of WarsawWarsaw; Poland; 11 August 2014 - 14 August 2014, 2014, s. 46-53.
[76]
M. Khelghatdoust och S. Girdzijauskas, "Short : Gossip-based sampling in social overlays," i Networked Systems : Second International Conference, NETYS 2014, Marrakech, Morocco, May 15–17, 2014, Revised Selected Papers, 2014, s. 335-340.
[77]
F. Rahimian et al., "JA-BE-JA : A Distributed Algorithm for Balanced Graph Partitioning," i 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 2013 IEEE, 2013, s. 51-60.
[78]
F. Rahimian, T. L. Nguyen Huu och S. Girdzijauskas, "Locality Awareness in a Peer-to-Peer Publish/Subscribe System," i Distributed applications and interoperable systems : 12th IFIP WG 6.1 International Conference, DAIS 2012, Stockholm, Sweden, June 13-16, 2012. Proceedings, 2012, s. 45-58.
[79]
F. Rahimian et al., "Subscription Awareness Meets Rendezvous Routing," i AP2PS 2012,The Fourth International Conference on Advances in P2P Systems, 2012, s. 1-10.
[80]
F. Rahimian et al., "Vitis : A Gossip-based Hybrid Overlay for Internet-scale Publish/Subscribe Enabling Rendezvous Routing in Unstructured Overlay Networks," i Proceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011, 2011, s. 746-757.
[81]
S. Girdzijauskas et al., "Gravity: An Interest-Aware Publish/Subscribe System Based on Structured Overlays," i Proceedings of the Second International Conference on Distributed Event-Based Systems, DEBS 2008, 2008.
[82]
F. Klemm et al., "On Routing in Distributed Hash Tables," i Peer-to-Peer Computing, 2007. P2P 2007. Seventh IEEE International Conference on, 2007, s. 113-122.
[83]
S. Girdzijauskas, A. Datta och K. Aberer, "Oscar : A Data-Oriented Overlay For Heterogeneous Environments," i 2007 IEEE 23RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3, 2007, s. 1365-1367.
[84]
M. Steinle et al., "Mapping Moving Landscapes by Mining Mountains of Logs : Novel Techniques for Dependency Model Generation," i The 32nd International Conference on Very Large Data Bases, September 12-15, 2006, Seoul, Korea., 2006, s. 1093-1102.
[85]
S. Girdzijauskas, A. Datta och K. Aberer, "Oscar : Small-world overlay for realistic key distributions," i The Fourth International Workshop on Databases, Information Systems and Peer-to-Peer Computing, September 11, 2006, Seoul, Korea, 2006, s. 247-258.
[86]
S. Girdzijauskas, A. Datta och K. Aberer, "On Small World Graphs in Non-uniformly Distributed Key Spaces," i Proceedings - International Workshop on Biomedical Data Engineering, BMDE2005, 2005.
[87]
K. Aberer et al., "The Essence of P2P : A Reference Architecture for Overlay Networks," i Fifth IEEE International Conference on Peer-to-Peer Computing, Proceedings, 2005, s. 11-20.
[88]
A. Datta, S. Girdzijauskas och K. Aberer, "On de Bruijn routing in distributed hash tables : There and back again," i The 4th IEEE International Conference on Peer-to-Peer Computing, proceedings, 2004, s. 159-166.

Icke refereegranskade

Konferensbidrag

[89]
S. Girdzijauskas et al., "Magnet : Practical Subscription Clustering for Internet-Scale Publish/Subscribe," i DEBS '10 Proceedings of the Fourth ACM International Conference on Distributed Event-Based Systems, 2010, s. 172-183.

Rapporter

[90]
A. Soliman och S. Girdzijauskas, "Adaptive Graph-based algorithms for Spam Detection in Social Networks," KTH Royal Institute of Technology, 2016.
[91]
A. Soliman et al., "DIVa: Decentralized Identity Validation for Social Networks," KTH Royal Institute of Technology, 2015.
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