Knowledge is often highly specific to the conditions of acquisition, so there is limited transfer of learning from training to testing. A series of studies is reported examining specificity and transfer of learning in three very different tasks, including digit data entry, speeded aiming, and time...
Language transfer in language learning Susan M. GassLarry Selinker Jan 1985 1. List of Contributors 2. Preface 3. Introduction (by Gass, Susan M.) 4. A Role for the Mother Tongue (by Corder, S. Pit) 5. A New Account of Language Transfer (by Schachter, Jacquelyn) 6. Verification of ...
We propose a rule-based learning model to explain perceptual learning and its specificity and transfer. In this model, a decision unit in high-level brain areas learns the rules of reweighting the V1 inputs through training. However, these rules cannot be applied to a new orientation/location...
Loss of Specificity: While transfer learning can be great for generalization, it might lose some task-specific details. For example, if a model is trained to identify animals in general, it might not perform well at recognizing rare species because it hasn’t been exposed to them. Complexity:...
NT occurs if TL results in worse performance; otherwise, it is a positive transfer. Interestingly, NT was not first studied in machine learning; instead, it has been a widely studied topic in educational psychology [19], [20]. Take language learning for example, NT occurs when learning in ...
DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series [arxiv] Domain adaptation for anomaly detection 使用域自适应进行时间序列异常检测 CVPR'24 Unified Language-driven Zero-shot Domain Adaptation [arxiv] Language-driven zero-shot domain adaptation 语言驱动的零样...
Contrastive learning in protein language space predicts interactions between drugs and protein targets. Proc. Natl Acad. Sci. USA 120, e2220778120 (2023). Google Scholar Minervina, A. A. et al. SARS-CoV-2 antigen exposure history shapes phenotypes and specificity of memory CD8+ T cells. ...
Transfer learning from one game to the others proved possible although one game appeared slightly less generalizable. Finally, offline ERP analyses revealed differences in the early (visual) components, which we relate to each game graphical specificity. In contrast, all games did involve a strong ...
Transfer learning for crack detection without image enhancement A model created for one job is utilized as the basis for another task in transfer learning, a machine learning technique55,56,57. The use of pre-trained models as the foundation for computer vision and natural language processing task...
we here develop a deep transfer learning method to predict the inter-chain contacts of transmembrane proteins, named DeepTMP, which first trains an initial model on a large number of soluble proteins and then transfers it to transmembrane proteins by utilizing the features of protein language model...