activity
20082025
most citedA self-organising eigenspace map for time series clustering

1 citations · 1 across the 3 of their papers we have counts for

collaborators

8 papers

cs.LG2025

DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads

Antonio Guillen-Perez, Avisek Naug, Vineet Gundecha +8

The increasing energy demands and carbon footprint of large-scale AI require intelligent workload management in globally distributed data centers. Yet progress is limited by the ab…

cs.DC2025

Trace Replay Simulation of MIT SuperCloud for Studying Optimal Sustainability Policies

Wesley Brewer, Matthias Maiterth, Damien Fay

The rapid growth of AI supercomputing is creating unprecedented power demands, with next-generation GPU datacenters requiring hundreds of megawatts and producing fast, large swings…

stat.ML2019★ 1 cited

A self-organising eigenspace map for time series clustering

Donya Rahmani, Damien Fay, Jacek Brodzki

This paper presents a novel time series clustering method, the self-organising eigenspace map (SOEM), based on a generalisation of the well-known self-organising feature map (SOFM)…

cs.LG2018

Automated Adaptation Strategies for Stream Learning

Rashid Bakirov, Bogdan Gabrys, Damien Fay

Automation of machine learning model development is increasingly becoming an established research area. While automated model selection and automated data pre-processing have been…

cs.SI2015

An exploration of fetish social networks and communities

Damien Fay, Hamed Haddadi, Michael C. Seto +2

Online Social Networks (OSNs) provide a venue for virtual interactions and relationships between individuals. In some communities, OSNs also facilitate arranging online meetings an…

cs.DS2015

Predictive partitioning for efficient BFS traversal in social networks

Damien Fay

In this paper we show how graph structure can be used to drastically reduce the computational bottleneck of the Breadth First Search algorithm (the foundation of many graph travers…