Search Results for author:
Found 4 papers, 1 papers with code
Class-Prototype Conditional Diffusion Model with Gradient Projection for Continual Learning
To address this, we propose the Gradient Projection Class-Prototype Conditional Diffusion Model (GPPDM), a GR-based approach for continual learning that enhances image quality in generators and thus reduces the CF in classifiers.
KOPPA: Improving Prompt-based Continual Learning with Key-Query Orthogonal Projection and Prototype-based One-Versus-All
Drawing inspiration from prompt tuning techniques applied to Large Language Models, recent methods based on pre-trained ViT networks have achieved remarkable results in the field of Continual Learning.
Continual Learning with Optimal Transport based Mixture Model
To address this issue, in this work, we first propose an online mixture model learning approach based on nice properties of the mature optimal transport theory (OT-MM).
From Implicit to Explicit feedback: A deep neural network for modeling sequential behaviours and long-short term preferences of online users
In addition, we go from the hypothesis that a user's preference at a time is a combination of long-term and short-term interests.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
