Multiagent Router Throttling: Decentralized Coordinated Response Against DDoS Attacks. - Kleanthis Malialis; Daniel Kudenko (IAAI, 2013)

Coordinated Team Learning and Difference Rewards for Distributed Intrusion Response. - Kleanthis Malialis; Sam Devlin; Daniel Kudenko (ECAI, 2014)

Distributed reinforcement learning for network intrusion response. - Kleanthis Malialis (2014)

Distributed reinforcement learning for adaptive and robust network intrusion response. - Kleanthis Malialis; Sam Devlin; Daniel Kudenko (Connect. Sci., 2015)

Distributed response to network intrusions using multiagent reinforcement learning. - Kleanthis Malialis; Daniel Kudenko (Eng. Appl. Artif. Intell., 2015)

Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. - Kleanthis Malialis; Sam Devlin; Daniel Kudenko (AAMAS, 2016)

Feature Selection as a Multiagent Coordination Problem. - Kleanthis Malialis; Jun Wang 012; Gary Brooks; George Frangou (CoRR, 2016)

Real-Time Bidding by Reinforcement Learning in Display Advertising. - Han Cai; Kan Ren; Weinan Zhang 001; Kleanthis Malialis; Jun Wang 012; Yong Yu 001; Defeng Guo (WSDM, 2017)

Queue-Based Resampling for Online Class Imbalance Learning. - Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou (ICANN (1), 2018)

Data-efficient Online Classification with Siamese Networks and Active Learning. - Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou (IJCNN, 2020)

Online Learning With Adaptive Rebalancing in Nonstationary Environments. - Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou (IEEE Trans. Neural Networks Learn. Syst., 2021)

A Multi-label Time Series Classification Approach for Non-intrusive Water End-Use Monitoring. - Dimitris Papatheodoulou; Pavlos Pavlou; Stelios G. Vrachimis; Kleanthis Malialis; Demetrios G. Eliades; Theocharis Theocharides (AIAI (2), 2022)

Data Augmentation On-the-fly and Active Learning in Data Stream Classification. - Kleanthis Malialis; Dimitris Papatheodoulou; Stylianos Filippou; Christos G. Panayiotou; Marios M. Polycarpou (SSCI, 2022)

A Hybrid Active-Passive Approach to Imbalanced Nonstationary Data Stream Classification. - Kleanthis Malialis; Manuel Roveri; Cesare Alippi; Christos G. Panayiotou; Marios M. Polycarpou (SSCI, 2022)

Nonstationary data stream classification with online active learning and siamese neural networks. - Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou (CoRR, 2022)

Nonstationary data stream classification with online active learning and siamese neural networks✩. - Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou (Neurocomputing, 2022)

A Study of Data-Driven Methods for Adaptive Forecasting of COVID-19 Cases. - Charithea Stylianides; Kleanthis Malialis; Panayiotis Kolios (ICANN (1), 2023)

Improving Customer Experience in Call Centers with Intelligent Customer-Agent Pairing. - Stylianos Filippou; Andreas Tsiartas; Petros Hadjineophytou; Spyros Christofides; Kleanthis Malialis; Christos G. Panayiotou (AIAI (1), 2023)

Autoencoder-based Anomaly Detection in Streaming Data with Incremental Learning and Concept Drift Adaptation. - Jin Li; Kleanthis Malialis; Marios M. Polycarpou (IJCNN, 2023)

Unsupervised Unlearning of Concept Drift with Autoencoders. - André Artelt; Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou; Barbara Hammer (SSCI, 2023)

A Machine Learning Approach for Detecting GPS Location Spoofing Attacks in Autonomous Vehicles. - Stylianos Filippou; A. Achilleos; Syeda Zillay Nain Zukhraf; Christos Laoudias; Kleanthis Malialis; Maria K. Michael; George Ellinas (VTC2023-Spring, 2023)

Time-varying compartmental models with neural networks for pandemic infection forecasting. - Marianna Karapitta; Andreas Kasis; Charithea Stylianides; Kleanthis Malialis; Panayiotis Kolios (EMBC, 2024)

Self-Supervised Learning from Incrementally Drifting Data Streams. - Valerie Vaquet; Jonas Vaquet; Fabian Hinder; Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou; Barbara Hammer (ESANN, 2024)

Unsupervised Incremental Learning with Dual Concept Drift Detection for Identifying Anomalous Sequences. - Jin Li; Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou (IJCNN, 2024)

Incremental Learning with Concept Drift Detection and Prototype-based Embeddings for Graph Stream Classification. - Kleanthis Malialis; Jin Li; Christos G. Panayiotou; Marios M. Polycarpou (IJCNN, 2024)

Cooperative Search and Track of Rogue Drones using Multiagent Reinforcement Learning. - Panayiota Valianti; Kleanthis Malialis; Panayiotis Kolios; Georgios Ellinas (SMC, 2024)

Cooperative Multi-Agent Jamming of Multiple Rogue Drones Using Reinforcement Learning. - Panayiota Valianti; Kleanthis Malialis; Panayiotis Kolios; Georgios Ellinas (IEEE Trans. Mob. Comput., 2024)

SiameseDuo++: Active learning from data streams with dual augmented siamese networks. - Kleanthis Malialis; Stylianos Filippou; Christos G. Panayiotou; Marios M. Polycarpou (Neurocomputing, 2025)

Urban Water Consumption Forecasting Using Deep Learning and Correlated District Metered Areas. - Kleanthis Malialis; Nefeli Mavri; Stelios G. Vrachimis; Marios S. Kyriakou; Demetrios G. Eliades; Marios M. Polycarpou (CoRR, 2025)

Online Detection of Water Contamination Under Concept Drift. - Jin Li; Kleanthis Malialis; Stelios G. Vrachimis; Marios M. Polycarpou (CoRR, 2025)

Transformer-based Multivariate Time Series Anomaly Localization. - Charalampos Shimillas; Kleanthis Malialis; Konstantinos Fokianos; Marios M. Polycarpou (CoRR, 2025)

Investigating Forecasting Models for Pandemic Infections Using Heterogeneous Data Sources: A 2-year Study with COVID-19. - Zacharias Komodromos; Kleanthis Malialis; Panayiotis Kolios (CoRR, 2025)