Zobrazeno 1 - 10
of 3 069
pro vyhledávání: '"Di Noia"'
Autor:
Mancino, Alberto Carlo Maria, Bufi, Salvatore, Di Fazio, Angela, Malitesta, Daniele, Pomo, Claudio, Ferrara, Antonio, Di Noia, Tommaso
Thanks to the great interest posed by researchers and companies, recommendation systems became a cornerstone of machine learning applications. However, concerns have arisen recently about the need for reproducibility, making it challenging to identif
Externí odkaz:
http://arxiv.org/abs/2410.22972
In recent years, 3D models have gained popularity in various fields, including entertainment, manufacturing, and simulation. However, manually creating these models can be a time-consuming and resource-intensive process, making it impractical for lar
Externí odkaz:
http://arxiv.org/abs/2409.19322
Autor:
Attimonelli, Matteo, Danese, Danilo, Di Fazio, Angela, Malitesta, Daniele, Pomo, Claudio, Di Noia, Tommaso
In specific domains like fashion, music, and movie recommendation, the multi-faceted features characterizing products and services may influence each customer on online selling platforms differently, paving the way to novel multimodal recommendation
Externí odkaz:
http://arxiv.org/abs/2409.15857
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