Results 61 to 70 of about 208,309 (312)
Hybrid Collaborative Filtering with Autoencoders [PDF]
, 2016 Collaborative Filtering aims at exploiting the feedback of users to provide personalised recommendations. Such algorithms look for latent variables in a large sparse matrix of ratings.
Gaudel, Romaric +2 more
core +3 more sources
BMI‐1 modulation and trafficking during M phase in diffuse intrinsic pontine glioma
FEBS Open Bio, EarlyView.The schematic illustrates BMI‐1 phosphorylation during M phase, which triggers its translocation from the nucleus to the cytoplasm. In cycling cells, BMI‐1 functions within the PRC1 complex to mediate H2A K119 monoubiquitination. Following PTC596‐induced M phase arrest, phosphorylated BMI‐1 dissociates from PRC1 and is exported to the cytoplasm via its
Banlanjo Umaru +6 more
wiley +1 more source
Perceptron Collaborative Filtering
International Journal for Research in Applied Science and Engineering Technology, 2023 Abstract: While multivariate logistic regression classifiers are a great way of implementing collaborative filtering - a method of making automatic predictions about the interests of a user by collecting preferences or taste information from many other users, we can also achieve similar results using neural networks.
openaire +2 more sources
SNUPN‐Related Muscular Dystrophy: Novel Phenotypic, Pathological and Functional Protein Insights
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective SNUPN‐related muscular dystrophy or LGMDR29 is a new entity that covers from a congenital or childhood onset pure muscular dystrophy to more complex phenotypes combining neurodevelopmental features, cataracts, or spinocerebellar ataxia. So far, 12 different variants have been described.
Nuria Muelas +18 more
wiley +1 more source
RACOFI: A Rule-Applying Collaborative Filtering System [PDF]
, 2003 In this paper we give an overview of the RACOFI (Rule-Applying Collaborative Filtering) multidimensional rating system and its related technologies. This will be exemplified with RACOFI Music, an implemented collaboration agent that assists on-line users
Boley, Harold, Lemire, Daniel
core
Collaborative filtering via sparse Markov random fields
, 2016 Recommender systems play a central role in providing individualized access to information and services. This paper focuses on collaborative filtering, an approach that exploits the shared structure among mind-liked users and similar items. In particular,
Phung, Dinh +2 more
core +1 more source
Functional Connectivity Linked to Cognitive Recovery After Minor Stroke
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Patients with minor stroke exhibit slowed processing speed and generalized alterations in functional connectivity involving frontoparietal cortex (FPC). The pattern of connectivity evolves over time. In this study, we examine the relationship of functional connectivity patterns to cognitive performance, to determine ...
Vrishab Commuri +7 more
wiley +1 more source
Stability of matrix factorization for collaborative filtering [PDF]
, 2012 We study the stability vis a vis adversarial noise of matrix factorization algorithm for matrix completion. In particular, our results include: (I) we bound the gap between the solution matrix of the factorization method and the ground truth in terms of ...
Wang, Yu-Xiang, Xu, Huan
core
OBOE: Collaborative Filtering for AutoML Model Selection
, 2019 Algorithm selection and hyperparameter tuning remain two of the most challenging tasks in machine learning. Automated machine learning (AutoML) seeks to automate these tasks to enable widespread use of machine learning by non-experts.
Akimoto, Yuji +3 more
core +1 more source
Collaborative Filtering Bandits [PDF]
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016 The 39th SIGIR (SIGIR 2016)
Li, Shuai +2 more
openaire +2 more sources