18 citations · 25 across the 5 of their papers we have counts for
6 papers
Improving Continual Learning of Knowledge Graph Embeddings via Informed Initialization
Gerard Pons, Besim Bilalli, Anna Queralt
Many Knowledege Graphs (KGs) are frequently updated, forcing their Knowledge Graph Embeddings (KGEs) to adapt to these changes. To address this problem, continual learning techniqu…
Knowledge Graphs for Enhancing Large Language Models in Entity Disambiguation
Gerard Pons, Besim Bilalli, Anna Queralt
Recent advances in Large Language Models (LLMs) have positioned them as a prominent solution for Natural Language Processing tasks. Notably, they can approach these problems in a z…
Towards Continuous Experiment-driven MLOps
Keerthiga Rajenthiram, Milad Abdullah, Ilias Gerostathopoulos +5
Despite advancements in MLOps and AutoML, ML development still remains challenging for data scientists. First, there is poor support for and limited control over optimizing and evo…
Capturing and Anticipating User Intents in Data Analytics via Knowledge Graphs
Gerard Pons, Besim Bilalli, Anna Queralt
In today's data-driven world, the ability to extract meaningful information from data is becoming essential for businesses, organizations and researchers alike. For that purpose, a…
A data-science pipeline to enable the Interpretability of Many-Objective Feature Selection
Uchechukwu F. Njoku, Alberto Abelló, Besim Bilalli +1
Many-Objective Feature Selection (MOFS) approaches use four or more objectives to determine the relevance of a subset of features in a supervised learning task. As a consequence, M…
PRESISTANT: Learning based assistant for data pre-processing
Besim Bilalli, Alberto Abelló, Tomàs Aluja-Banet +1
Data pre-processing is one of the most time consuming and relevant steps in a data analysis process (e.g., classification task). A given data pre-processing operator (e.g., transfo…