516 citations · 595 across the 16 of their papers we have counts for
16 papers
Online Convex Optimisation: The Optimal Switching Regret for all Segmentations Simultaneously
Stephen Pasteris, Chris Hicks, Vasilios Mavroudis +1
We consider the classic problem of online convex optimisation. Whereas the notion of static regret is relevant for stationary problems, the notion of switching regret is more appro…
Bandits with Abstention under Expert Advice
Stephen Pasteris, Alberto Rumi, Maximilian Thiessen +4
We study the classic problem of prediction with expert advice under bandit feedback. Our model assumes that one action, corresponding to the learner's abstention from play, has no…
Multi-class Graph Clustering via Approximated Effective -Resistance
Shota Saito, Mark Herbster
This paper develops an approximation to the (effective) -resistance and applies it to multi-class clustering. Spectral methods based on the graph Laplacian and its generalizatio…
Adversarial Online Collaborative Filtering
Stephen Pasteris, Fabio Vitale, Mark Herbster +2
We investigate the problem of online collaborative filtering under no-repetition constraints, whereby users need to be served content in an online fashion and a given user cannot b…
Improved Regret Bounds for Tracking Experts with Memory
James Robinson, Mark Herbster
We address the problem of sequential prediction with expert advice in a non-stationary environment with long-term memory guarantees in the sense of Bousquet and Warmuth [4]. We giv…
Online Multitask Learning with Long-Term Memory
Mark Herbster, Stephen Pasteris, Lisa Tse
We introduce a novel online multitask setting. In this setting each task is partitioned into a sequence of segments that is unknown to the learner. Associated with each segment is…