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pro vyhledávání: '"Di Noia A"'
Item recommendation (the task of predicting if a user may interact with new items from the catalogue in a recommendation system) and link prediction (the task of identifying missing links in a knowledge graph) have long been regarded as distinct prob
Externí odkaz:
http://arxiv.org/abs/2409.07433
Autor:
Abbattista, Davide, Anelli, Vito Walter, Di Noia, Tommaso, Macdonald, Craig, Petrov, Aleksandr Vladimirovich
In the realm of music recommendation, sequential recommender systems have shown promise in capturing the dynamic nature of music consumption. Nevertheless, traditional Transformer-based models, such as SASRec and BERT4Rec, while effective, encounter
Externí odkaz:
http://arxiv.org/abs/2409.04329
Autor:
Malitesta, Daniele, Rossi, Emanuele, Pomo, Claudio, Di Noia, Tommaso, Malliaros, Fragkiskos D.
Generally, items with missing modalities are dropped in multimodal recommendation. However, with this work, we question this procedure, highlighting that it would further damage the pipeline of any multimodal recommender system. First, we show that t
Externí odkaz:
http://arxiv.org/abs/2408.11767
Autor:
Malitesta, Daniele, Pomo, Claudio, Anelli, Vito Walter, Mancino, Alberto Carlo Maria, Di Noia, Tommaso, Di Sciascio, Eugenio
Recently, graph neural networks (GNNs)-based recommender systems have encountered great success in recommendation. As the number of GNNs approaches rises, some works have started questioning the theoretical and empirical reasons behind their superior
Externí odkaz:
http://arxiv.org/abs/2408.11762
The increasing demand for online fashion retail has boosted research in fashion compatibility modeling and item retrieval, focusing on matching user queries (textual descriptions or reference images) with compatible fashion items. A key challenge is
Externí odkaz:
http://arxiv.org/abs/2408.09847
Autor:
Balabdaoui, Fadoua, Di Noia, Antonio
In shape-constrained nonparametric inference, it is often necessary to perform preliminary tests to verify whether a probability mass function (p.m.f.) satisfies qualitative constraints such as monotonicity, convexity or in general $k$-monotonicity.
Externí odkaz:
http://arxiv.org/abs/2407.01751
Robust Bayesian analysis has been mainly devoted to detecting and measuring robustness to the prior distribution. Indeed, many contributions in the literature aim to define suitable classes of priors which allow the computation of variations of quant
Externí odkaz:
http://arxiv.org/abs/2405.15141
The Intrinsic Dimension (ID) is a key concept in unsupervised learning and feature selection, as it is a lower bound to the number of variables which are necessary to describe a system. However, in almost any real-world dataset the ID depends on the
Externí odkaz:
http://arxiv.org/abs/2405.15132
Estimation and goodness-of-fit testing for positive random variables with explicit Laplace transform
Many flexible families of positive random variables exhibit non-closed forms of the density and distribution functions and this feature is considered unappealing for modelling purposes. However, such families are often characterized by a simple expre
Externí odkaz:
http://arxiv.org/abs/2405.15041
The integration of Large Language Models (LLMs) into healthcare diagnostics offers a promising avenue for clinical decision-making. This study outlines the development of a novel method for zero-shot/few-shot in-context learning (ICL) by integrating
Externí odkaz:
http://arxiv.org/abs/2405.06270