Trace-Norm Regularized Multi-Task Learning for Sea State Bias Estimation
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Ocean University of China"
DOI: 10.1007/s11802-020-4267-x
Abstract: Sea state bias (SSB) is an important component of errors for the radar altimeter measurements of sea surface height (SSH). However, existing SSB estimation methods are almost all based on single-task learning (STL), where one… read more here.
Keywords: multi task; estimation; task; task learning ... See more keywords
"You're wrong, I'll switch, I'm wrong, I'll stay": How task-switching strategies are modulated by a partner in a multi-task learning protocol.
Sign Up to like & getrecommendations! Published in 2021 at "Acta psychologica"
DOI: 10.1016/j.actpsy.2021.103475
Abstract: Individuals given control over practice variables make practice decisions based on their current performance. When individuals practice in pairs, the question as to if and how a partner's performance impacts these decisions is of theoretical… read more here.
Keywords: partner; task learning; learning protocol; multi task ... See more keywords
Interference in early dual-task learning by predatory mites
Sign Up to like & getrecommendations! Published in 2017 at "Animal behaviour"
DOI: 10.1016/j.anbehav.2017.09.005
Abstract: Animals are commonly exposed to multiple environmental stimuli, but whether, and under which circumstances, they can attend to multiple stimuli in multitask learning challenges is elusive. Here, we assessed whether simultaneously occurring chemosensory stimuli interfere… read more here.
Keywords: dual task; presence; task learning; predatory mites ... See more keywords
Joint monitoring of multiple quality-related indicators in nonlinear processes based on multi-task learning
Sign Up to like & getrecommendations! Published in 2020 at "Measurement"
DOI: 10.1016/j.measurement.2020.108158
Abstract: Abstract Current strategies for quality-related process monitoring mainly focus on a single quality indicator. For multiple related indicators, traditional algorithms extract the same quality-related features from variable spaces while neglecting the specific features of each… read more here.
Keywords: multi task; quality; quality related; task learning ... See more keywords
Self-calibrated brain network estimation and joint non-convex multi-task learning for identification of early Alzheimer's disease
Sign Up to like & getrecommendations! Published in 2020 at "Medical image analysis"
DOI: 10.1016/j.media.2020.101652
Abstract: Detection of early stages of Alzheimer's disease (AD) (i.e., mild cognitive impairment (MCI)) is important to maximize the chances to delay or prevent progression to AD. Brain connectivity networks inferred from medical imaging data have… read more here.
Keywords: multi task; brain network; network estimation; task learning ... See more keywords
Co-evolutionary multi-task learning with predictive recurrence for multi-step chaotic time series prediction
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.02.065
Abstract: Abstract Multi-task learning employs a shared representation of knowledge for learning several instances of the same problem. Multi-step time series problem is one of the most challenging problems for machine learning methods. The performance of… read more here.
Keywords: multi task; step; task learning; prediction ... See more keywords
End-to-end aspect-based sentiment analysis with hierarchical multi-task learning
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2021.03.100
Abstract: Abstract End-to-end aspect-based sentiment analysis(E2E-ABSA) is a sequence labeling task which detects aspect terms and the corresponding sentiment simultaneously. Previous works ignore the useful task-specific knowledge and embed the vital aspect and sentiment attributes implicitly… read more here.
Keywords: task learning; sentiment; task; multi task ... See more keywords
Spike prediction on primary motor cortex from medial prefrontal cortex during task learning
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ac8180
Abstract: Objectives. Brain–machine interfaces (BMIs) aim to help people with motor disabilities by interpreting brain signals into motor intentions using advanced signal processing methods. Currently, BMI users require intensive training to perform a pre-defined task, not… read more here.
Keywords: task; mpfc; task learning; motor ... See more keywords
Dataset-aware multi-task learning approaches for biomedical named entity recognition
Sign Up to like & getrecommendations! Published in 2020 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa515
Abstract: MOTIVATION Named entity recognition (NER) is a critical and fundamental task for biomedical text-mining. Recently, researchers have focused on exploiting deep neural networks for biomedical named entity recognition (Bio-NER). The performance of deep neural networks… read more here.
Keywords: multi task; task; task learning; bio ner ... See more keywords
Generative Multi-Task Learning for Text Classification
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2991337
Abstract: Multi-task learning leverages potential correlations among related tasks to extract common features and yield performance gains. In this paper, a generative multi-task learning (MTL) approach for text classification and categorization is proposed, which is composed… read more here.
Keywords: task learning; multi; multi task; classification ... See more keywords
Design of Efficient Speech Emotion Recognition Based on Multi Task Learning
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3237268
Abstract: Speech emotion recognition technology includes feature extraction and classifier construction. However, the recognition efficiency is reduced due to noise interference and gender differences. To solve this problem, this paper used two multi-task learning models based… read more here.
Keywords: recognition; task; task learning; multi task ... See more keywords