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09/11/2023
Formalizing Multimedia Recommendation through Multimodal Deep Learning
Recommender systems (RSs) offer personalized navigation experiences on o...
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09/07/2023
Evaluating ChatGPT as a Recommender System: A Rigorous Approach
Recent popularity surrounds large AI language models due to their impres...
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08/21/2023
A Topology-aware Analysis of Graph Collaborative Filtering
The successful integration of graph neural networks into recommender sys...
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08/01/2023
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis
The success of graph neural network-based models (GNNs) has significantl...
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03/28/2023
Machine-learned Adversarial Attacks against Fault Prediction Systems in Smart Electrical Grids
In smart electrical grids, fault detection tasks may have a high impact ...
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02/16/2023
Counterfactual Reasoning for Bias Evaluation and Detection in a Fairness under Unawareness setting
Current AI regulations require discarding sensitive features (e.g., gend...
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02/16/2023
Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning
The increasing application of Artificial Intelligence and Machine Learni...
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01/17/2023
MAFUS: a Framework to predict mortality risk in MAFLD subjects
Metabolic (dysfunction) associated fatty liver disease (MAFLD) establish...
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09/04/2022
Interactive Question Answering Systems: Literature Review
Question answering systems are recognized as popular and frequently effe...
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07/13/2022
URANUS: Radio Frequency Tracking, Classification and Identification of Unmanned Aircraft Vehicles
Safety and security issues for Critical Infrastructures (CI) are growing...
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07/29/2021
Sparse Feature Factorization for Recommender Systems with Knowledge Graphs
Deep Learning and factorization-based collaborative filtering recommenda...
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09/11/2019
How to make latent factors interpretable by feeding Factorization machines with knowledge graphs
Model-based approaches to recommendation can recommend items with a very...
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09/05/2019
On the discriminative power of Hyper-parameters in Cross-Validation and how to choose them
Hyper-parameters tuning is a crucial task to make a model perform at its...
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07/17/2018
Knowledge-aware Autoencoders for Explainable Recommender Sytems
Recommender Systems have been widely used to help users in finding what ...
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07/13/2018
Computing recommendations via a Knowledge Graph-aware Autoencoder
In the last years, deep learning has shown to be a game-changing technol...
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07/11/2018
The importance of being dissimilar in Recommendation
Similarity measures play a fundamental role in memory-based nearest neig...
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07/11/2018
