Results 161 to 170 of about 1,099,722 (325)
Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning [PDF]
, 2022 Sergio Rozada +2 more
openalex +1 more source
, 2010 We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that rankings of data induced by dis- tance from a query can be optimized against various ranking measures, such as AUC, Precision-at-k, MRR, MAP or NDCG.
Mcfee, Brian, Lanckriet, Gert
openaire +1 more source
Learning-to-Rank with Nested Feedback
Many platforms on the web present ranked lists of content to users, typically optimized for engagement-, satisfaction- or retention- driven metrics. Advances in the Learning-to-Rank (LTR) research literature have enabled rapid growth in this application area.
Hitesh Sagtani +2 more
openaire +2 more sources
Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett +8 more
wiley +1 more source
Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank. [PDF]
IEEE J Biomed Health Inform, 2020 Li Y +12 more
europepmc +1 more source
Arthritis Care &Research, EarlyView.This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah +5 more
wiley +1 more source
Learning to Rank Answers to Non-Factoid Questions from Web Collections
Computational Linguistics, 2021 Mihai Surdeanu +2 more
doaj +1 more source
Noise-resistant and scalable collective preference learning via ranked voting in swarm robotics [PDF]
, 2022 Qihao Shan, Sanaz Mostaghim
openalex +1 more source
Arthritis Care &Research, EarlyView.Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim +18 more
wiley +1 more source
Arthritis Care &Research, EarlyView.Objective Australian evidence on lived and care experiences of chronic musculoskeletal shoulder pain (CMSP), irrespective of disorder classification or disease, is limited. However, such evidence is important for person‐centered care and informing local service pathways and care guidelines or standards.
Sonia Ranelli +8 more
wiley +1 more source