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cs.LG2024
Perturbing the Gradient for Alleviating Meta Overfitting
Manas Gogoi, Sambhavi Tiwari, Shekhar Verma
The reason for Meta Overfitting can be attributed to two factors: Mutual Non-exclusivity and the Lack of diversity, consequent to which a single global function can fit the support…
cs.LG2023★ 1 cited
Learning to Learn with Indispensable Connections
Sambhavi Tiwari, Manas Gogoi, Shekhar Verma +1
Meta-learning aims to solve unseen tasks with few labelled instances. Nevertheless, despite its effectiveness for quick learning in existing optimization-based methods, it has seve…
cs.LG2022★ 2 cited
MAC: A Meta-Learning Approach for Feature Learning and Recombination
S. Tiwari, M. Gogoi, S. Verma +1
Optimization-based meta-learning aims to learn an initialization so that a new unseen task can be learned within a few gradient updates. Model Agnostic Meta-Learning (MAML) is a be…