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cs.LG2024
A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks
Uday Kiran Reddy Tadipatri, Benjamin D. Haeffele, Joshua Agterberg +1
We propose a general framework for deriving generalization bounds for parallel positively homogeneous neural networks--a class of neural networks whose input-output map decomposes…
cs.LG2024
LoRanPAC: Low-rank Random Features and Pre-trained Models for Bridging Theory and Practice in Continual Learning
Liangzu Peng, Juan Elenter, Joshua Agterberg +2
The goal of continual learning (CL) is to train a model that can solve multiple tasks presented sequentially. Recent CL approaches have achieved strong performance by leveraging la…