14 citations · 32 across the 14 of their papers we have counts for
14 papers
PROSE: A Theory of Optimal Stopping with Perishable Evidence for Peer Selection in Intermittently Connected Decentralised Learning
Christos Anagnostopoulos
Decentralised federated learning removes the aggregation server but makes collaboration dependent on transient peer availability. In mobile and intermittently connected systems, ev…
Improving Sequential Query Recommendation with Immediate User Feedback
Shameem A Puthiya Parambath, Christos Anagnostopoulos, Roderick Murray-Smith
We propose an algorithm for next query recommendation in interactive data exploration settings, like knowledge discovery for information gathering. The state-of-the-art query recom…
Local Learning at the Network Edge for Efficient & Secure Real-Time Predictive Analytics
Natascha Harth, Hans-Joerg Voegel, Kostas Kolomvatsos +1
The ability to perform computation on devices, such as smartphones, cars, or other nodes present at the Internet of Things leads to constraints regarding bandwidth, storage, and en…
Max-Utility Based Arm Selection Strategy For Sequential Query Recommendations
Shameem A. Puthiya Parambath, Christos Anagnostopoulos, Roderick Murray-Smith +2
We consider the query recommendation problem in closed loop interactive learning settings like online information gathering and exploratory analytics. The problem can be naturally…
A Proactive Management Scheme for Data Synopses at the Edge
Kostas Kolomvatsos, Christos Anagnostopoulos
The combination of the infrastructure provided by the Internet of Things (IoT) with numerous processing nodes present at the Edge Computing (EC) ecosystem opens up new pathways to…
A Soft Method for Outliers Detection at the Edge of the Network
Kostas Kolomvatsos, Christos Anagnostopoulos
The combination of the Internet of Things and the Edge Computing gives many opportunities to support innovative applications close to end users. Numerous devices present in both in…
On the Road from Edge Computing to the Edge Mesh
Panagiotis Oikonomou, Anna Karanika, Christos Anagnostopoulos +1
Nowadays, we are witnessing the advent of the Internet of Things (EC) with numerous devices performing interactions between them or with end users. The huge number of devices leads…
An Intelligent Edge-Centric Queries Allocation Scheme based on Ensemble Models
Kostas Kolomvatsos, Christos Anagnostopoulos
The combination of Internet of Things (IoT) and Edge Computing (EC) can assist in the delivery of novel applications that will facilitate end users activities. Data collected by nu…
Data Synopses Management based on a Deep Learning Model
Panagiotis Fountas, Kostas Kolomvatsos, Christos Anagnostopoulos
Pervasive computing involves the placement of processing services close to end users to support intelligent applications. With the advent of the Internet of Things (IoT) and the Ed…
Proactive Tasks Management based on a Deep Learning Model
Kostas Kolomvatsos, Christos Anagnotopoulos
Pervasive computing applications deal with intelligence surrounding users that can facilitate their activities. This intelligence is provided in the form of software components inc…
On the Use of Interpretable Machine Learning for the Management of Data Quality
Anna Karanika, Panagiotis Oikonomou, Kostas Kolomvatsos +1
Data quality is a significant issue for any application that requests for analytics to support decision making. It becomes very important when we focus on Internet of Things (IoT)…
ML-AQP: Query-Driven Approximate Query Processing based on Machine Learning
Fotis Savva, Christos Anagnostopoulos, Peter Triantafillou
As more and more organizations rely on data-driven decision making, large-scale analytics become increasingly important. However, an analyst is often stuck waiting for an exact res…
Adaptive Learning of Aggregate Analytics under Dynamic Workloads
Fotis Savva, Christos Anagnostopoulos, Peter Triantafillou
Large organizations have seamlessly incorporated data-driven decision making in their operations. However, as data volumes increase, expensive big data infrastructures are called t…
Explaining Aggregates for Exploratory Analytics
Fotis Savva, Christos Anagnostopoulos, Peter Triantafillou
Analysts wishing to explore multivariate data spaces, typically pose queries involving selection operators, i.e., range or radius queries, which define data subspaces of possible i…