Online Sum-Product Computation Over Trees. - Mark Herbster; Stephen Pasteris; Fabio Vitale (NIPS, 2012)

Online Similarity Prediction of Networked Data from Known and Unknown Graphs. - Claudio Gentile; Mark Herbster; Stephen Pasteris (COLT, 2013)

Fast Product Format. - Stephen Pasteris (CoRR, 2013)

Online Prediction at the Limit of Zero Temperature. - Mark Herbster; Stephen Pasteris; Shaona Ghosh (NIPS, 2015)

Predicting a switching sequence of graph labelings. - Mark Herbster; Stephen Pasteris; Massimiliano Pontil (J. Mach. Learn. Res., 2015)

Mistake Bounds for Binary Matrix Completion. - Mark Herbster; Stephen Pasteris; Massimiliano Pontil (NIPS, 2016)

Efficient algorithms for online learning over graphs. - Stephen Pasteris (2016)

Data distribution and scheduling for distributed analytics tasks. - Stephen Pasteris; Shiqiang Wang 001; Christian Makaya; Kevin Chan 001; Mark Herbster (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, 2017)

On Pairwise Clustering with Side Information. - Stephen Pasteris; Fabio Vitale; Claudio Gentile; Mark Herbster (CoRR, 2017)

On Similarity Prediction and Pairwise Clustering. - Stephen Pasteris; Fabio Vitale; Claudio Gentile; Mark Herbster (ALT, 2018)

MaxHedge: Maximising a Maximum Online with Theoretical Performance Guarantees. - Stephen Pasteris; Fabio Vitale; Kevin Chan 001; Shiqiang Wang 001 (CoRR, 2018)

MaxHedge: Maximizing a Maximum Online. - Stephen Pasteris; Fabio Vitale; Kevin S. Chan; Shiqiang Wang 001; Mark Herbster (AISTATS, 2019)

Multicast-Based Weight Inference in General Network Topologies. - Yilei Lin; Ting He 001; Shiqiang Wang 001; Kevin S. Chan; Stephen Pasteris (ICC, 2019)

Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems. - Stephen Pasteris; Shiqiang Wang 001; Mark Herbster; Ting He 001 (INFOCOM, 2019)

Communication-efficient k-Means for Edge-based Machine Learning. - Hanlin Lu; Ting He 001; Shiqiang Wang 001; Changchang Liu; Mehrdad Mahdavi; Vijaykrishnan Narayanan; Kevin S. Chan; Stephen Pasteris (ICDCS, 2020)

Joint Coreset Construction and Quantization for Distributed Machine Learning. - Hanlin Lu; Changchang Liu; Shiqiang Wang 001; Ting He 001; Vijaykrishnan Narayanan; Kevin S. Chan; Stephen Pasteris (Networking, 2020)

Online Multitask Learning with Long-Term Memory. - Mark Herbster; Stephen Pasteris; Lisa Tse (NeurIPS, 2020)

Online Matrix Completion with Side Information. - Mark Herbster; Stephen Pasteris; Lisa Tse (NeurIPS, 2020)

Looking Glass of NFV: Inferring the Structure and State of NFV Network From External Observations. - Yilei Lin; Ting He 001; Shiqiang Wang 001; Kevin Chan 001; Stephen Pasteris (IEEE/ACM Trans. Netw., 2020)

Online Learning of Facility Locations. - Stephen Pasteris; Ting He 001; Fabio Vitale; Shiqiang Wang 001; Mark Herbster (ALT, 2021)

A Gang of Adversarial Bandits. - Mark Herbster; Stephen Pasteris; Fabio Vitale; Massimiliano Pontil (NeurIPS, 2021)

Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback. - Lin Yang 013; Yu-Zhen Janice Chen; Stephen Pasteris; Mohammad H. Hajiesmaili; John C. S. Lui; Don Towsley (NeurIPS, 2021)

Joint Coreset Construction and Quantization for Distributed Machine Learning. - Hanlin Lu; Changchang Liu; Shiqiang Wang 001; Ting He 001; Vijay Narayanan; Kevin S. Chan; Stephen Pasteris (CoRR, 2022)

Communication-Efficient $k$k-Means for Edge-Based Machine Learning. - Hanlin Lu; Ting He 001; Shiqiang Wang 001; Changchang Liu; Mehrdad Mahdavi; Vijaykrishnan Narayanan; Kevin S. Chan; Stephen Pasteris (IEEE Trans. Parallel Distributed Syst., 2022)

Perceptronic Complexity and Online Matrix Completion. - Stephen Pasteris (ALT, 2023)

Nearest Neighbour with Bandit Feedback. - Stephen Pasteris; Chris Hicks; Vasilios Mavroudis (NeurIPS, 2023)

Regret Guarantees for Adversarial Online Collaborative Filtering. - Stephen Pasteris; Fabio Vitale; Mark Herbster; Claudio Gentile (CoRR, 2023)

A Hierarchical Nearest Neighbour Approach to Contextual Bandits. - Stephen Pasteris; Chris Hicks; Vasilios Mavroudis (CoRR, 2023)

Sum-max Submodular Bandits. - Stephen U. Pasteris; Alberto Rumi; Fabio Vitale; Nicolò Cesa-Bianchi (AISTATS, 2024)

Adversarial Online Collaborative Filtering. - Stephen Pasteris; Fabio Vitale; Mark Herbster; Claudio Gentile; André Panisson (ALT, 2024)

Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously. - Stephen Pasteris; Chris Hicks; Vasilios Mavroudis; Mark Herbster (NeurIPS, 2024)

Bandits with Abstention under Expert Advice. - Stephen Pasteris; Alberto Rumi; Maximilian Thiessen; Shota Saito; Atsushi Miyauchi 001; Fabio Vitale; Mark Herbster (NeurIPS, 2024)

Fusion Encoder Networks. - Stephen Pasteris; Chris Hicks; Vasilios Mavroudis (CoRR, 2024)

Fair Exploration and Exploitation. - Stephen Pasteris; Chris Hicks; Vasilios Mavroudis (CoRR, 2024)

Guidelines for Applying RL and MARL in Cybersecurity Applications. - Vasilios Mavroudis; Gregory Palmer; Sara Farmer; Kez Smithson Whitehead; David Foster; Adam Price; Ian Miles; Alberto Caron; Stephen Pasteris (CoRR, 2025)