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Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. [1] For example, for image classification , knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.
Zero transfer occurs when prior learning has no influence on new learning. Near: Near transfer occurs when many elements overlap between the conditions in which the learner obtained the knowledge or skill and the new situation. Far: Far transfer occurs when the new situation is very different from that in which learning occurred. Literal ...
Distinction between usual machine learning setting and transfer learning, and positioning of domain adaptation. Domain adaptation [1] [2] [3] is a field associated with machine learning and transfer learning. This scenario arises when we aim at learning a model from a source data distribution and applying that model on a different (but related ...
In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data. [1] Fine-tuning can be done on the entire neural network, or on only a subset of its layers, in which case the layers that are not being fine-tuned are "frozen" (i.e., not changed during backpropagation). [2]
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.
A common test for negative transfer is the AB-AC list learning paradigm from the verbal learning research of the 1950s and 1960s. In this paradigm, two lists of paired associates are learned in succession, and if the second set of associations (List 2) constitutes a modification of the first set of associations (List 1), negative transfer results and thus the learning rate of the second list ...
In machine learning, knowledge distillation or model distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have more knowledge capacity than small models, this capacity might not be fully utilized. It can be just as ...
Terraria (/ t ə ˈ r ɛər i ə / ⓘ tə-RAIR-ee-ə [1]) is a 2011 action-adventure sandbox game developed by Re-Logic. The game was first released for Windows and has since been ported to other PC and console platforms.