338 citations · 698 across the 54 of their papers we have counts for
12 papers · 1 filter
Bayesian Active Summarization
Alexios Gidiotis, Grigorios Tsoumakas
Bayesian Active Learning has had significant impact to various NLP problems, but nevertheless it's application to text summarization has been explored very little. We introduce Bay…
Short-term Renewable Energy Forecasting in Greece using Prophet Decomposition and Tree-based Ensembles
Argyrios Vartholomaios, Stamatis Karlos, Eleftherios Kouloumpris +1
Energy production using renewable sources exhibits inherent uncertainties due to their intermittent nature. Nevertheless, the unified European energy market promotes the increasing…
Harvesting the Public MeSH Note field
Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas +1
In this document, we report an analysis of the Public MeSH Note field of the new descriptors introduced in the MeSH thesaurus between 2006 and 2020. The aim of this analysis was to…
Self-citation Analysis using Sentence Embeddings
Athanasios Lagopoulos, Grigorios Tsoumakas
The purpose of citation indexes and metrics is intended to be a measure for scientific innovation and quality for researchers, journals, and institutions. However, those metrics ar…
Should We Trust This Summary? Bayesian Abstractive Summarization to The Rescue
Alexios Gidiotis, Grigorios Tsoumakas
We explore the notion of uncertainty in the context of modern abstractive summarization models, using the tools of Bayesian Deep Learning. Our approach approximates Bayesian infere…
Optimizing Area Under the Curve Measures via Matrix Factorization for Predicting Drug-Target Interaction with Multiple Similarities
Bin Liu, Grigorios Tsoumakas
In drug discovery, identifying drug-target interactions (DTIs) via experimental approaches is a tedious and expensive procedure. Computational methods efficiently predict DTIs and…
VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance
Spyridon Paraschos, Ioannis Mollas, Nick Bassiliades +1
The use of machine learning rapidly increases in high-risk scenarios where decisions are required, for example in healthcare or industrial monitoring equipment. In crucial situatio…
LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information
Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas
Artificial Intelligence (AI) has a tremendous impact on the unexpected growth of technology in almost every aspect. AI-powered systems are monitoring and deciding about sensitive e…
Conclusive Local Interpretation Rules for Random Forests
Ioannis Mollas, Nick Bassiliades, Grigorios Tsoumakas
In critical situations involving discrimination, gender inequality, economic damage, and even the possibility of casualties, machine learning models must be able to provide clear i…
Improving Zero-Shot Entity Retrieval through Effective Dense Representations
Eleni Partalidou, Despina Christou, Grigorios Tsoumakas
Entity Linking (EL) seeks to align entity mentions in text to entries in a knowledge-base and is usually comprised of two phases: candidate generation and candidate ranking. While…
Improving Distantly-Supervised Relation Extraction through BERT-based Label & Instance Embeddings
Despina Christou, Grigorios Tsoumakas
Distantly-supervised relation extraction (RE) is an effective method to scale RE to large corpora but suffers from noisy labels. Existing approaches try to alleviate noise through…
What is all this new MeSH about? Exploring the semantic provenance of new descriptors in the MeSH thesaurus
Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas +1
The Medical Subject Headings (MeSH) thesaurus is a controlled vocabulary widely used in biomedical knowledge systems, particularly for semantic indexing of scientific literature. A…