Results 11 to 20 of about 1,987,455 (278)
Clústeres regionales como estrategia para superar desventajas competitivas
Revista de Investigación, Desarrollo e Innovación, 2020 El artículo tiene el objetivo de identificar cuáles son las ventajas de los clúster regionales para incentivar la competitividad de las empresas. Metodológicamente, se aborda un enfoque cualitativo a través de un ejercicio bibliométrico, que permitió la:
Diana Lorena Pineda-Ospina +2 more
doaj +2 more sources
BERTopic: Neural topic modeling with a class-based TF-IDF procedure [PDF]
arXiv.org, 2022 Topic models can be useful tools to discover latent topics in collections of documents. Recent studies have shown the feasibility of approach topic modeling as a clustering task.
M. Grootendorst
semanticscholar +1 more source
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Units [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2021 Self-supervised approaches for speech representation learning are challenged by three unique problems: (1) there are multiple sound units in each input utterance, (2) there is no lexicon of input sound units during the pre-training phase, and (3) sound ...
Wei-Ning Hsu +5 more
semanticscholar +1 more source
AAAI Conference on Artificial Intelligence, 2021 In this paper, we propose an online clustering method called Contrastive Clustering (CC) which explicitly performs the instance- and cluster-level contrastive learning.
Yunfan Li +5 more
semanticscholar +1 more source
antiSMASH 6.0: improving cluster detection and comparison capabilities
Nucleic Acids Res., 2021 Many microorganisms produce natural products that form the basis of antimicrobials, antivirals, and other drugs. Genome mining is routinely used to complement screening-based workflows to discover novel natural products.
K. Blin +6 more
semanticscholar +1 more source
Encyclopedia of Gerontology and Population Aging, 2021 • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely ...
J. Vermunt, J. Magidson
semanticscholar +1 more source
An Efficient Framework for Clustered Federated Learning [PDF]
IEEE Transactions on Information Theory, 2020 We address the problem of federated learning (FL) where users are distributed and partitioned into clusters. This setup captures settings where different groups of users have their own objectives (learning tasks) but by aggregating their data with others
Avishek Ghosh +3 more
semanticscholar +1 more source
Clustered Federated Learning: Model-Agnostic Distributed Multitask Optimization Under Privacy Constraints [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2019 Federated learning (FL) is currently the most widely adopted framework for collaborative training of (deep) machine learning models under privacy constraints.
Felix Sattler, K. Müller, W. Samek
semanticscholar +1 more source
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks [PDF]
Knowledge Discovery and Data Mining, 2019 Graph convolutional network (GCN) has been successfully applied to many graph-based applications; however, training a large-scale GCN remains challenging.
Wei-Lin Chiang +5 more
semanticscholar +1 more source
Pfam: The protein families database in 2021
Nucleic Acids Res., 2020 The Pfam database is a widely used resource for classifying protein sequences into families and domains. Since Pfam was last described in this journal, over 350 new families have been added in Pfam 33.1 and numerous improvements have been made to ...
Jaina Mistry +11 more
semanticscholar +1 more source