Felipe Kenji Nakano

A semantic-based community model for high-fidelity tuning of olfactory mixture distances

Vahid Satarifard, Laura Sisson, Yikun Han, Pedro Ilídio et autres

A central goal in sensory science is to establish quantitative mappings between physical stimuli and perceptual experience. Although such mappings are well defined in vision and audition, they remain elusive in olfaction, particularly for complex odor mixtures. Here, we show that perceptual …

us, be, mm, fr, gb, se, br, es, jo, ca, il, ch (code pays fourni par la source)

Personalizing Second Language Learning: Integrating AI with Learner Preference, Proficiency, and Engagement

Alireza Gharahighehi, Pedro Ilídio, Sameh Said-Metwaly, Ann‐Sophie Noreillie et autres

Personalization has become a cornerstone of online learning platforms, offering tailored experiences that enhance learner engagement, satisfaction, and performance. Moving beyond one-size-fits-all approaches, personalized systems can provide flexible access, improve efficiency, and support both cognitive and non-cognitive development. In language learning, personalization …

be (code pays fourni par la source)

Personalizing Second Language Learning: Integrating AI with Learner Preference, Proficiency, and Engagement

Alireza Gharahighehi, Pedro Ilídio, Sameh Said-Metwaly, Ann‐Sophie Noreillie et autres

Personalization has become a cornerstone of online learning platforms, offering tailored experiences that enhance learner engagement, satisfaction, and performance. Moving beyond one-size-fits-all approaches, personalized systems can provide flexible access, improve efficiency, and support both cognitive and non-cognitive development. In language learning, personalization …

be (code pays fourni par la source)

Investigating Study Choice in Flemish Schools: An Application of Multi-Target Regression and Large Language Models

Bert Vos, Felipe Kenji Nakano, Celine Vens, Alireza Gharahighehi

status: Published

be, mm (code pays fourni par la source)

Oxytrees: Model Trees for Bipartite Learning

Pedro Ilídio, Felipe Kenji Nakano, Alireza Gharahighehi, Robbe D'hondt et autres

Bipartite learning is a machine learning task that aims to predict interactions between pairs of instances. It has been applied to various domains, including drug-target interactions, RNA-disease associations, and regulatory network inference. Despite being widely investigated, current methods still present drawbacks, as …

nl, br (code pays fourni par la source)

Oxytrees: Model Trees for Bipartite Learning

Pedro de Carvalho Braga Ilídio, Felipe Kenji Nakano, Alireza Gharahighehi, Robbe D’hondt et autres

sponsorship: The work received funding from the Flemish Government (AI Research Program), VOEWIAI02. The authors thank FWO, 11A7U26N, 1235924N and 1S38025N. R.C. thanks the Brazilian National Council for Scientific and Technological Development (CNPq), grant number 300934/2025-4, and the Sao Paulo Research Foundation …

nl, be, mm, br (code pays fourni par la source)

Autoassociative Random Forest Clustering

Robbe D’hondt, Felipe Kenji Nakano, Celine Vens

nl, be (code pays fourni par la source)

High-Fidelity Tuning of Olfactory Mixture Distances in the Perceptual Space of Smell Through a Community Effort

Vahid Satarifard, Pedro Ilídio, Matej Hladiš, Maxence Lalis et autres

Abstract A central goal in sensory science is to establish quantitative mappings between physical stimuli and perceptual responses. While such mappings are well characterized in vision and audition, they remain poorly defined in olfaction, limiting progress toward understanding the representations of smell. …

us, be, fr, se, ca, mm, il (code pays fourni par la source)

Oxytrees: Model Trees for Bipartite Learning

Pedro Ilídio, Felipe Kenji Nakano, Alireza Gharahighehi, Robbe D’hondt et autres

Bipartite learning is a machine learning task that aims to predict interactions between pairs of instances. It has been applied to various domains, including drug-target interactions, RNA-disease associations, and regulatory network inference. Despite being widely investigated, current methods still present drawbacks, as …

Pairwise and Attribute-Aware Decision Tree-Based Preference Elicitation for Cold-Start Recommendation

Alireza Gharahighehi, Felipe Kenji Nakano, Xuehua Yang, Wenhan Cu et autres

Recommender systems (RSs) are intelligent filtering methods that suggest items to users based on their inferred preferences, derived from their interaction history on the platform. Collaborative filtering-based RSs rely on users past interactions to generate recommendations. However, when a user is new …

Correction: Development and validation of a machine learning model for early prediction of intensive care unit acquired weakness

Felipe Kenji Nakano, Nathalie Van Aerde, Grégoire Coppens, Ilse Vanhorebeek et autres

be, mm, nl (code pays fourni par la source)

Development and validation of a machine learning model for early prediction of intensive care unit acquired weakness

Felipe Kenji Nakano, Nathalie Van Aerde, Grégoire Coppens, Ilse Vanhorebeek et autres

BACKGROUND: Early identification of potential high cost and high need patients on the ICU may assist in the development of targeted protocols, which allows proper resource utilization and initialization of preventive care. Weakness acquired in the ICU developed within the first week …

nl, be, mm (code pays fourni par la source)