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SupplementaryMaterialfor SuperLoss: AGenericLoss forRobustCurriculumLearning
For the baseline, we have used the default parameters from detectron2.
Visual Prompt Tuning in Null Space for Continual Learning Yue Lu
To be concrete, we firstly take the full self-attention and LayerNorm into consideration and derive a strict condition for eliminating the interference through a comprehensive analysis of the forward propagation of the ViT layer. Then we further propose to convert the condition of self-attention into its two sufficient conditions, which enables us to address the challenge of high order and nonlinearity.
S-Prompts LearningwithPre-trainedTransformers: AnOccam'sRazorforDomainIncrementalLearning
However,learning multiple tasks insequence, generally called continual learning,remainsasubstantial challenge fordeeplearning.
Heavy-tailed Representations,TextPolarity Classification&DataAugmentation
Representing the meaning of natural language in a mathematically grounded way is a scientific challenge that has received increasing attention withthe explosion of digital content and text data in the last decade.
Heavy-tailed Representations,TextPolarity Classification&DataAugmentation
Representing the meaning of natural language in a mathematically grounded way is a scientific challenge that has received increasing attention withthe explosion of digital content and text data in the last decade.