Results 81 to 90 of about 1,101,099 (365)
Learning to rank music tracks using triplet loss
, 2020 Most music streaming services rely on automatic recommendation algorithms to exploit their large music catalogs. These algorithms aim at retrieving a ranked list of music tracks based on their similarity with a target music track.
Peeters, Geoffroy +2 more
core +1 more source
From omics to AI—mapping the pathogenic pathways in type 2 diabetes
FEBS Letters, EarlyView.Integrating multi‐omics data with AI‐based modelling (unsupervised and supervised machine learning) identify optimal patient clusters, informing AI‐driven accurate risk stratification. Digital twins simulate individual trajectories in real time, guiding precision medicine by matching patients to targeted therapies.
Siobhán O'Sullivan +2 more
wiley +1 more source
Towards intelligent geospatial data discovery: a machine learning framework for search ranking
International Journal of Digital Earth, 2018 Current search engines in most geospatial data portals tend to induce users to focus on one single-data characteristic dimension (e.g. popularity and release date).
Yongyao Jiang +8 more
doaj +1 more source
Deep Multi-view Learning to Rank
, 2019 We study the problem of learning to rank from multiple information sources. Though multi-view learning and learning to rank have been studied extensively leading to a wide range of applications, multi-view learning to rank as a synergy of both topics has
Cao, Guanqun +4 more
core +1 more source
International Journal of Approximate Reasoning, 2018 Abstract Learning parameters associated with propositions is one of the main tasks of probabilistic logic programming (PLP), and learning algorithms for PLP have been primarily developed based on maximum likelihood estimation or the optimization of discriminative criteria.
Ryosuke Kojima, Taisuke Sato
openaire +1 more source
FEBS Letters, EarlyView.Spinal muscular atrophy (SMA) is a genetic disease affecting motor neurons. Individuals with SMA experience mitochondrial dysfunction and oxidative stress. The aim of the study was to investigate the effect of an antioxidant and neuroprotective substance, ergothioneine (ERGO), on an SMNΔ7 mouse model of SMA.
Francesca Cadile +8 more
wiley +1 more source
Is Learning to Rank Worth It? A Statistical Analysis of Learning to Rank Methods
, 2013 The Learning to Rank (L2R) research field has experienced a fast paced growth over the last few years, with a wide variety of benchmark datasets and baselines available for experimentation. We here investigate the main assumption behind this field, which is that, the use of sophisticated L2R algorithms and models, produce significant gains over more ...
Gomes, Guilherme de Castro Mendes +3 more
openaire +2 more sources
FEBS Letters, EarlyView.Angiotensin II (AngII), a neuropeptide, interacts with amyloid‐β (Aβ), a key player in Alzheimer's disease. This study reveals that AngII reduces Aβ aggregation and membrane disruption in vitro. Biophysical assays and molecular modeling suggest AngII binds disordered Aβ forms, potentially modulating early amyloidogenic events and contributing to ...
Mohsen Habibnia +5 more
wiley +1 more source
PlayerRank: Leveraging Learning-to-Rank AI for Player Positioning in Cricket
IEEE AccessPlayer prioritization is crucial in sports analysis, yet prioritizing based on playing position is underexplored. This paper focuses on using learning-to-rank machine learning models to select the best players for slots within a cricket team’s ...
Bilal Hassan +4 more
doaj +1 more source
Query Optimization Algorithm Based on Learning to Rank [PDF]
Jisuanji kexueQuery optimization is a key aspect of relational databases.In the traditional query optimization process,cardinality estimation of join and filter operations in a query is usually required in order to obtain a better execution plan.However,due to the ...
YU Yang, PENG Yuwei
doaj +1 more source