Results 31 to 40 of about 5,803,394 (295)
Multitask learning and benchmarking with clinical time series data [PDF]
Scientific Data, 2017 Health care is one of the most exciting frontiers in data mining and machine learning. Successful adoption of electronic health records (EHRs) created an explosion in digital clinical data available for analysis, but progress in machine learning for ...
Hrayr Harutyunyan +3 more
semanticscholar +1 more source
Attention-Guided Multitask Learning for Surface Defect Identification
IEEE Transactions on Industrial Informatics, 2023 Surface defect identification is an essential task in the industrial quality control process, in which visual checks are conducted on a manufactured product to ensure that it meets quality standards.
Vignesh Sampath +5 more
semanticscholar +1 more source
Cross-lingual transfer learning and multitask learning for capturing multiword expressions [PDF]
, 2019 This is an accepted manuscript of an article published by Association for Computational Linguistics in Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019), available online: https://www.aclweb.org/anthology/W19-5119 ...
Ha, Le An +2 more
core +1 more source
Distilling Knowledge with a Teacher’s Multitask Model for Biomedical Named Entity Recognition
Information, 2023 Single-task models (STMs) struggle to learn sophisticated representations from a finite set of annotated data. Multitask learning approaches overcome these constraints by simultaneously training various associated tasks, thereby learning generic ...
Tahir Mehmood +4 more
doaj +1 more source
Parallel learning by multitasking neural networks
Journal of Statistical Mechanics: Theory and Experiment, 2023 Abstract Parallel learning, namely the simultaneous learning of multiple patterns, constitutes a modern challenge for neural networks. While this cannot be accomplished by standard Hebbian associative neural networks, in this paper we show how the multitasking Hebbian network (a variation on the theme of the Hopfield ...
Agliari E. +3 more
openaire +4 more sources
Unsupervised online multitask learning of behavioral sentence embeddings [PDF]
PeerJ Computer Science, 2019 Appropriate embedding transformation of sentences can aid in downstream tasks such as NLP and emotion and behavior analysis. Such efforts evolved from word vectors which were trained in an unsupervised manner using large-scale corpora.
Shao-Yen Tseng +2 more
doaj +2 more sources
IEEE Sensors Journal, 2023 Bolts are frequently subjected to loosening due to time varying external loads during service. The electromechanical impedance (EMI) technique based on piezoelectric ceramic wafers (PZT) is sensitive to the initial bolt preload looseness.
Fei Du +4 more
semanticscholar +1 more source
IEEE Access, 2021 This paper proposes a data-driven, condition-based maintenance framework (DCBM) for deteriorating equipment under the impact of varying environments and natural aging. The equipment's degradation status is determined by a prognostic and health monitoring
Lei Zhang, Jianguo Zhang
doaj +1 more source
Vision Transformer Adapters for Generalizable Multitask Learning [PDF]
IEEE International Conference on Computer Vision, 2023 We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains.
Deblina Bhattacharjee +2 more
semanticscholar +1 more source
Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity
Abstract and Applied Analysis, 2014 We address object tracking problem as a multitask feature learning process based on low-rank representation of features with joint sparsity. We first select features with low-rank representation within a number of initial frames to obtain subspace basis.
Hyuncheol Kim, Joonki Paik
doaj +1 more source