2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data Sets.
Xiaoxi WeiA. Aldo FaisalMoritz Grosse-WentrupAlexandre GramfortSylvain ChevallierVinay JayaramCamille JeunetStylianos BakasSiegfried LudwigKonstantinos BarmpasMehdi BahriYannis PanagakisNikolaos A. LaskarisDimitrios A. AdamosStefanos ZafeiriouWilliam C. DuongStephen M. GordonVernon J. LawhernMaciej SliwowskiVincent RouannePiotr TempczykPublished in: CoRR (2022)
Keyphrases
- transfer learning
- data sets
- learning tasks
- knowledge transfer
- data sources
- labeled data
- cross domain
- collaborative filtering
- reinforcement learning
- active learning
- machine learning
- transfer knowledge
- text classification
- semi supervised learning
- manifold alignment
- multi task learning
- structure learning
- target domain
- machine learning algorithms
- training data
- high dimensional data
- transferring knowledge
- cross domain learning
- domain adaptation
- real world
- semi supervised
- training set
- learning algorithm
- multi task
- text categorization
- conditional independence
- feature selection
- unlabeled data
- object recognition
- data streams