Results 51 to 60 of about 1,093,151 (324)
ViTOR: Learning to Rank Webpages Based on Visual Features [PDF]
, 2019 The visual appearance of a webpage carries valuable information about its quality and can be used to improve the performance of learning to rank (LTR).
Akker, Bram van den +2 more
core +2 more sources
Learning to Rank with BERT for Argument Quality Evaluation
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 The task of argument quality ranking, which identifies the quality of free text arguments, remains, to this day, a challenge. While most state-of-the-art initiatives use point-wise ranking methods and predict an absolute quality score for each argument ...
Charles-Olivier Favreau +2 more
doaj +1 more source
Unbiased Learning to Rank with Unbiased Propensity Estimation
, 2018 Learning to rank with biased click data is a well-known challenge. A variety of methods has been explored to debias click data for learning to rank such as click models, result interleaving and, more recently, the unbiased learning-to-rank framework ...
Ai, Qingyao +4 more
core +1 more source
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
Pediatric Blood &Cancer, EarlyView.ABSTRACT Introduction We developed MedSupport, a multilevel medication adherence intervention designed to address root barriers to medication adherence. This study sought to explore the feasibility and acceptability of the MedSupport intervention strategies to support a future full‐scale randomized controlled trial.
Elizabeth G. Bouchard +8 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
Early Exit Strategies for Learning-to-Rank Cascades
IEEE Access, 2023 The ranking pipelines of modern search platforms commonly exploit complex machine-learned models and have a significant impact on the query response time.
Francesco Busolin +5 more
doaj +1 more source
Differentiable Unbiased Online Learning to Rank
, 2018 Online Learning to Rank (OLTR) methods optimize rankers based on user interactions. State-of-the-art OLTR methods are built specifically for linear models. Their approaches do not extend well to non-linear models such as neural networks.
de Rijke, Maarten, Oosterhuis, Harrie
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Cyclophosphamide (CY) is associated with potentially fatal cardiotoxicity, yet no electrocardiographic indices have been established for early detection of CY‐induced cardiomyopathy. This study aimed to determine whether corrected QT interval (QTc) prolongation can predict early onset of CY‐related cardiac dysfunction in pediatric ...
Junpei Kawamura +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