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cs.LG2024
Mitigating the Bias in the Model for Continual Test-Time Adaptation
Inseop Chung, Kyomin Hwang, Jayeon Yoo +1
Continual Test-Time Adaptation (CTA) is a challenging task that aims to adapt a source pre-trained model to continually changing target domains. In the CTA setting, a model does no…
cs.LG2023★ 2 cited
SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning
JunHoo Lee, Jayeon Yoo, Nojun Kwak
In this paper, we hypothesize that gradient-based meta-learning (GBML) implicitly suppresses the Hessian along the optimization trajectory in the inner loop. Based on this hypothes…
cs.LG2021★ 3 cited
Dynamic Collective Intelligence Learning: Finding Efficient Sparse Model via Refined Gradients for Pruned Weights
Jangho Kim, Jayeon Yoo, Yeji Song +2
With the growth of deep neural networks (DNN), the number of DNN parameters has drastically increased. This makes DNN models hard to be deployed on resource-limited embedded system…