Publications by Sarunas Girdzijauskas

Peer reviewed

Articles

[1]

D. Roy, V. Komini and S. Girdzijauskas, "Classifying falls using out-of-distribution detection in human activity recognition," AI Communications, vol. 36, no. 4, pp. 251-267, 2023.

[2]

S. Yfantidou et al., "LifeSnaps, a 4-month multi-modal dataset capturing unobtrusive snapshots of our lives in the wild," Scientific Data, vol. 9, no. 1, 2022.

[3]

S. Zamboni et al., "Pedestrian trajectory prediction with convolutional neural networks," Pattern Recognition, vol. 121, 2022.

[4]

D. Roy, S. Girdzijauskas and S. Socolovschi, "Confidence-Calibrated Human Activity Recognition," Sensors, vol. 21, no. 19, pp. 6566-6566, 2021.

[5]

S. Antaris, D. Rafailidis and 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, pp. 259-273, 2010.

[11]

S. Girdzijauskas, A. Datta and 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.

Conference papers

[12]

M. Isaksson et al., "Adaptive Expert Models for Federated Learning," in Trustworthy Federated Learning : First International Workshop, FL 2022, 2023, pp. 1-16.

[13]

A. Samy, Z. T. Kefato and S. Girdzijauskas, "Data-Driven Self-Supervised Graph Representation Learning," in ECAI 2023 : 26th European Conference on Artificial Intelligence, including 12th Conference on Prestigious Applications of Intelligent Systems, PAIS 2023 - Proceedings, 2023, pp. 629-636.

[14]

E. Listo Zec et al., "Decentralized Adaptive Clustering of Deep Nets is Beneficial for Client Collaboration," in FL 2022 : Trustworthy Federated Learning, 2023, pp. 59-71.

[15]

M. Bonvalet, Z. T. Kefato and S. Girdzijauskas, "Graph2Feat : Inductive Link Prediction via Knowledge Distillation," in ACM Web Conference 2023 : Companion of the World Wide Web Conference, WWW 2023, 2023, pp. 805-812.

[16]

Y. Jin et al., "Learning Cellular Coverage from Real Network Configurations using GNNs," in 2023 IEEE 97th Vehicular Technology Conference, VTC 2023-Spring - Proceedings, 2023.

[17]

A. E. Samy and S. Girdzijauskas, "Mitigating Sybil Attacks in Federated Learning," in INFORMATION SECURITY PRACTICE AND EXPERIENCE, ISPEC 2023, 2023, pp. 36-51.

[18]

S. Pozzoli and S. Girdzijauskas, "On Learning Embeddings at the Intersection of Communities and Roles," in 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," in 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, pp. 352-358.

[20]

D. Roy and S. Girdzijauskas, "Temporal Differential Privacy for Human Activity Recognition," in 2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), Thessaloniki, Greece, 9 - 13 October 2023, 2023, pp. 1-10.

[21]

L. Giaretta et al., "Towards a Realistic Decentralized Naive Bayes with Differential Privacy," in E-Business and Telecommunications - 19th International Conference, ICSBT 2022, and 19th International Conference, SECRYPT 2022, Revised Selected Papers, 2023, pp. 98-121.

[22]

M. Isaksson et al., "Adaptive Expert Models for Personalization in Federated Learning," in 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," in LREC 2022 : Thirteen International Conference On Language Resources And Evaluation, 2022, pp. 6300-6309.

[24]

A. Stefanoni et al., "Detecting Security Patches in Java Projects Using NLP Technology," in ICNLSP 2022 : Proceedings of the 5th International Conference on Natural Language and Speech Processing, 2022, pp. 50-56.

[25]

T. Marchioro et al., "Federated Naive Bayes under Differential Privacy," in Proceedings of the 19th International Conference on Security and Cryptography - SECRYPT, 2022, pp. 170-180.

[26]

D. Roy and S. Girdzijauskas, "Mixing temporal experts for Human Activity Recognition," in 34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022, 2022, pp. 11-18.

[27]

S. Pozzoli and S. Girdzijauskas, "Not Only Degree Matters : Diffusion-Driven Role Recognition," in 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, pp. 16-24.

[28]

Y. Jin et al., "Open World Learning Graph Convolution for Latency Estimation in Routing Networks," in 2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2022.

[29]

D. Roy, V. Komini and S. Girdzijauskas, "Out-of-distribution in Human Activity Recognition," in 34th Workshop of the Swedish Artificial Intelligence Society, SAIS 2022, 2022, pp. 1-10.

[30]

A. Samy et al., "SchemaWalk : Schema Aware Random Walks for Heterogeneous Graph Embedding," in WWW 2022 - Companion Proceedings of the Web Conference 2022, 2022, pp. 1157-1166.

[31]

F. Cornell et al., "Symbolic Hyperdimensional Vectors with Sparse Graph Convolutional Neural Networks," in 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," in DE 2022 : Proceedings of the 1st International Workshop on Data Economy, Part of CoNEXT 2022, 2022, pp. 49-56.

[33]

L. Giaretta et al., "Towards a decentralized infrastructure for data marketplaces: narrowing the gap between academia and industry," in DE '22: Proceedings of the 1st International Workshop on Data Economy, 2022, pp. 49-56.

[34]

S. Antaris, D. Rafailidis and S. Girdzijauskas, "A Deep Graph Reinforcement Learning Model for Improving User Experience in Live Video Streaming," in 2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2021, pp. 1787-1796.

[35]

A. A. Alkathiri et al., "Decentralized Word2Vec Using Gossip Learning," in Proceedings of the 23^rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021), 2021.

[36]

Z. T. Kefato et al., "Dynamic embeddings for interaction prediction," in The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021, 2021, pp. 1609-1618.

[37]

L. Giaretta et al., "LiMNet : Early-Stage Detection of IoT Botnets with Lightweight Memory Networks," in 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 and S. Girdzijauskas, "Meta-reinforcement learning via buffering graph signatures for live video streaming events," in Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2021, 2021, pp. 385-392.

[39]

L. Giaretta et al., "PDS2 : A user-centered decentralized marketplace for privacy preserving data processing," in 2021 IEEE 37TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOPS (ICDEW 2021), 2021, pp. 92-99.

[40]

L. Giaretta et al., "PDS²: A user-centered decentralized marketplace for privacy preserving data processing," in 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 and S. Girdzijauskas, "Self-supervised Graph Neural Networks without explicit negative sampling," in The International Workshop on Self-Supervised Learning for the Web (SSL'21), at WWW'21, 2021.

[42]

Z. Lee, S. Girdzijauskas and P. Papapetrou, "Z-Embedding : A Spectral Representation of Event Intervals for Efficient Clustering and Classification," in Machine Learning And Knowledge Discovery In Databases, ECML PKDD 2020, Pt I, 2021, pp. 710-726.

[43]

A. Soliman et al., "Decentralized and Adaptive K-Means Clusteringfor Non-IID Data using HyperLogLog Counters," in Proceedings of The 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Singapore, 11-16 May 2020., 2020.

[44]

S. Antaris, D. Rafailidis and S. Girdzijauskas, "EGAD : Evolving Graph Representation Learning with Self-Attention and Knowledge Distillation for Live Video Streaming Events," in 2020 IEEE international conference on big data (big data), 2020, pp. 1455-1464.

[45]

Z. T. Kefato and S. Girdzijauskas, "Gossip and Attend: Context-Sensitive Graph Representation Learning," in In Proc. of the 14-th International AAAI Conference on Web and Social Media, ICWSM'20, 2020.

[46]

D. Montesi, S. Girdzijauskas and V. Vlassov, "Repeating Link Prediction over Dynamic Graphs," in 2020 IEEE International Conference on Big Data (Big Data), 2020, pp. 4420-4428.

[47]

L. Bahri and S. Girdzijauskas, "Blockchain technology : Practical P2P computing (Tutorial)," in Proceedings - 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems, FAS*W 2019, 2019, pp. 249-250.

[48]

L. Giaretta and S. Girdzijauskas, "Gossip Learning : Off the Beaten Path," in 2019 IEEE International Conference on Big Data (IEEE Big Data 2019), December 9-12, 2019, Los Angeles, CA, USA, 2019.

[49]

L. Bahri and S. Girdzijauskas, "Trust Mends Blockchains: Living up to Expectations," in IEEE 39th International Conference on Distributed Computing Systems (ICDCS), Dallas, July 7-10 2019, 2019.

[50]

L. Bahri and S. Girdzijauskas, "Trust mends blockchains : Living up to expectations," in Proceedings - International Conference on Distributed Computing Systems, 2019, pp. 1358-1368.

[51]

S. Girdzijauskas, G. Pallis and Y. Wu, "Welcome from the Program Chairs," in Proceedings - 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2019, 2019, pp. XVI-XVII.

[52]

C. Chen, Y. Tock and S. Girdzijauskas, "BeaConvey: Co-Design of Overlay and Routing for Topic-basedPublish/Subscribe on Small-World Networks," in 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," in 2018 FIFTH INTERNATIONAL CONFERENCE ON SOCIAL NETWORKS ANALYSIS, MANAGEMENT AND SECURITY (SNAMS), 2018, pp. 72-79.

[54]

Z. Kefato et al., "CaTS: Network-Agnostic Virality Prediction Model to Aid Rumour Detection," in International Workshop on Rumours and Deception in Social Media (RDSM 2018), 2018.

[55]

K. Sozinov, V. Vlassov and S. Girdzijauskas, "Human Activity Recognition Using Federated Learning," in 2018 IEEE INT CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, UBIQUITOUS COMPUTING & COMMUNICATIONS, BIG DATA & CLOUD COMPUTING, SOCIAL COMPUTING & NETWORKING, SUSTAINABLE COMPUTING & COMMUNICATIONS, 2018, pp. 1103-1111.

[56]

N. Apolonia et al., "SELECT : A distributed publish/subscribe notification system for online social networks," in Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018, 2018, pp. 970-979.

[57]

Z. Abbas et al., "Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks," in 2018 IEEE International Congress on Big Data (BigData Congress), 2018, pp. 57-65.

[58]

K. Ghoorchian and S. Girdzijauskas, "Spatio-Temporal Multiple Geo-Location Identification on Twitter," in Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, 2018, pp. 3412-3421.

[59]

A. Soliman, F. Rahimian and S. Girdzijauskas, "Stad: Stateful Diffusion for Linear Time Community Detection," in 38th IEEE International Conference on Distributed Computing Systems, 2018.

[60]

L. Bahri and S. Girdzijauskas, "When Trust Saves Energy - A Reference Framework for Proof-of-Trust (PoT) Blockchains," in WWW '18 Companion Proceedings of the The Web Conference 2018, 2018, pp. 1165-1169.

[61]

A. Soliman and S. Girdzijauskas, "Adagraph : Adaptive graph-based algorithms for spam detection in social networks," in 5th International Conference on Networked Systems, NETYS 2017, 2017, pp. 338-354.

[62]

K. Ghoorchian, S. Girdzijauskas and F. Rahimian, "DeGPar : Large Scale Topic Detection usingNode-Cut Partitioning on Dense Weighted Graphs," in 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), 2017, pp. 775-785.

[63]

M. A. U. Nasir et al., "Fully dynamic algorithm for top-k densest subgraphs," in CIKM '17 Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017, pp. 1817-1826.

[64]

N. Apolonia et al., "Gossip-based service monitoring platform for wireless edge cloud computing," in 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," in IEEE International Conference on Data Mining Workshops, ICDMW, 2017, pp. 623-630.

[66]

L. Bahri et al., "Beat the DIVa : Decentralized Identity Validation for Online Social Networks," in 2016 32ND IEEE INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2016, pp. 1330-1333.

[67]

A. Soliman and S. Girdzijauskas, "DLSAS: Distributed Large-Scale Anti-Spam Framework for Decentralized Online Social Networks," in 2016 IEEE 2ND INTERNATIONAL CONFERENCE ON COLLABORATION AND INTERNET COMPUTING (IEEE CIC), 2016, pp. 363-372.

[68]

N. Laleh et al., "Gossip-based behavioral group identification in decentralized OSNs," in 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, 2016, pp. 676-691.

[69]

A. Soliman et al., "DIVa : Decentralized Identity Validation for Social Networks," in PROCEEDINGS OF THE 2015 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING (ASONAM 2015), 2015, pp. 383-391.

[70]

M. Sedaghat et al., "Divide the task, multiply the outcome : Cooperative VM consolidation," in Proceedings of the International Conference on Cloud Computing Technology and Science, CloudCom, 2015, pp. 300-305.

[71]

K. Ghoorchian, F. Rahimian and S. Girdzijauskas, "Semi-Supervised Multiple Disambiguation," in IEEE Computer Society Conference Publishing Services, 2015.

[72]

M. A. U. Nasir and S. Girdzijauskas, "Socially-aware distributed hash tables for decentralized online social networks," in Peer-to-Peer Computing (P2P), 2015 IEEE International Conference on, 2015, pp. 1-10.

[73]

F. Rahimian et al., "Distributed Vertex-Cut Partitioning," in In the 14th IFIP international conference on Distributed Applications and Interoperable Systems (DAIS’14)., 2014, pp. 186-200.

[74]

M. A. U. Nasir, F. Rahimian and S. Girdzijauskas, "Gossip-based partitioning and replication for Online Social Networks," in ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2014, pp. 33-42.

[75]

F. Rahimian, S. Girdzijauskas and S. Haridi, "Parallel Community Detection For Cross-Document Coreference," in 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, pp. 46-53.

[76]

M. Khelghatdoust and S. Girdzijauskas, "Short : Gossip-based sampling in social overlays," in Networked Systems : Second International Conference, NETYS 2014, Marrakech, Morocco, May 15–17, 2014, Revised Selected Papers, 2014, pp. 335-340.

[77]

F. Rahimian et al., "JA-BE-JA : A Distributed Algorithm for Balanced Graph Partitioning," in 7th International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 2013 IEEE, 2013, pp. 51-60.

[78]

F. Rahimian, T. L. Nguyen Huu and S. Girdzijauskas, "Locality Awareness in a Peer-to-Peer Publish/Subscribe System," in Distributed applications and interoperable systems : 12th IFIP WG 6.1 International Conference, DAIS 2012, Stockholm, Sweden, June 13-16, 2012. Proceedings, 2012, pp. 45-58.

[79]

F. Rahimian et al., "Subscription Awareness Meets Rendezvous Routing," in AP2PS 2012,The Fourth International Conference on Advances in P2P Systems, 2012, pp. 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," in Proceedings - 25th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2011, 2011, pp. 746-757.

[81]

S. Girdzijauskas et al., "Gravity: An Interest-Aware Publish/Subscribe System Based on Structured Overlays," in 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," in Peer-to-Peer Computing, 2007. P2P 2007. Seventh IEEE International Conference on, 2007, pp. 113-122.

[83]

S. Girdzijauskas, A. Datta and K. Aberer, "Oscar : A Data-Oriented Overlay For Heterogeneous Environments," in 2007 IEEE 23RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3, 2007, pp. 1365-1367.

[84]

M. Steinle et al., "Mapping Moving Landscapes by Mining Mountains of Logs : Novel Techniques for Dependency Model Generation," in The 32nd International Conference on Very Large Data Bases, September 12-15, 2006, Seoul, Korea., 2006, pp. 1093-1102.

[85]

S. Girdzijauskas, A. Datta and K. Aberer, "Oscar : Small-world overlay for realistic key distributions," in The Fourth International Workshop on Databases, Information Systems and Peer-to-Peer Computing, September 11, 2006, Seoul, Korea, 2006, pp. 247-258.

[86]

S. Girdzijauskas, A. Datta and K. Aberer, "On Small World Graphs in Non-uniformly Distributed Key Spaces," in Proceedings - International Workshop on Biomedical Data Engineering, BMDE2005, 2005.

[87]

K. Aberer et al., "The Essence of P2P : A Reference Architecture for Overlay Networks," in Fifth IEEE International Conference on Peer-to-Peer Computing, Proceedings, 2005, pp. 11-20.

[88]

A. Datta, S. Girdzijauskas and K. Aberer, "On de Bruijn routing in distributed hash tables : There and back again," in The 4th IEEE International Conference on Peer-to-Peer Computing, proceedings, 2004, pp. 159-166.

Non-peer reviewed

Conference papers

[89]

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