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cs.LG2023★ 1 cited
Investigating the Impact of Weight Sharing Decisions on Knowledge Transfer in Continual Learning
Josh Andle, Ali Payani, Salimeh Yasaei-Sekeh
Continual Learning (CL) has generated attention as a method of avoiding Catastrophic Forgetting (CF) in the sequential training of neural networks, improving network efficiency and…
cs.LG2023
A Theoretical Perspective on Subnetwork Contributions to Adversarial Robustness
Jovon Craig, Josh Andle, Theodore S. Nowak +1
The robustness of deep neural networks (DNNs) against adversarial attacks has been studied extensively in hopes of both better understanding how deep learning models converge and i…
cs.LG2022
Theoretical Understanding of the Information Flow on Continual Learning Performance
Josh Andle, Salimeh Yasaei Sekeh
Continual learning (CL) is a setting in which an agent has to learn from an incoming stream of data sequentially. CL performance evaluates the model's ability to continually learn…