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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 3: AAAI-21 Technical Tracks 3

Few-Shot Lifelong Learning

February 1, 2023

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Authors

Pratik Mazumder

Department of Computer Science and Engineering, IIT Kanpur, India


Pravendra Singh

Independent Researcher, India


Piyush Rai

Department of Computer Science and Engineering, IIT Kanpur, India


DOI:

10.1609/aaai.v35i3.16334


Abstract:

Many real-world classification problems often have classes with very few labeled training samples. Moreover, all possible classes may not be initially available for training, and may be given incrementally. Deep learning models need to deal with this two-fold problem in order to perform well in real-life situations. In this paper, we propose a novel Few-Shot Lifelong Learning (FSLL) method that enables deep learning models to perform lifelong/continual learning on few-shot data. Our method selects very few parameters from the model for training every new set of classes instead of training the full model. This helps in preventing overfitting. We choose the few parameters from the model in such a way that only the currently unimportant parameters get selected. By keeping the important parameters in the model intact, our approach minimizes catastrophic forgetting. Furthermore, we minimize the cosine similarity between the new and the old class prototypes in order to maximize their separation, thereby improving the classification performance. We also show that integrating our method with self-supervision improves the model performance significantly. We experimentally show that our method significantly outperforms existing methods on the miniImageNet, CIFAR-100, and CUB-200 datasets. Specifically, we outperform the state-of-the-art method by an absolute margin of 19.27% for the CUB dataset.

Topics: AAAI

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HOW TO CITE:

Pratik Mazumder||Pravendra Singh||Piyush Rai Few-Shot Lifelong Learning Proceedings of the AAAI Conference on Artificial Intelligence (2021) 2337-2345.

Pratik Mazumder||Pravendra Singh||Piyush Rai Few-Shot Lifelong Learning AAAI 2021, 2337-2345.

Pratik Mazumder||Pravendra Singh||Piyush Rai (2021). Few-Shot Lifelong Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 2337-2345.

Pratik Mazumder||Pravendra Singh||Piyush Rai. Few-Shot Lifelong Learning. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.2337-2345.

Pratik Mazumder||Pravendra Singh||Piyush Rai. 2021. Few-Shot Lifelong Learning. "Proceedings of the AAAI Conference on Artificial Intelligence". 2337-2345.

Pratik Mazumder||Pravendra Singh||Piyush Rai. (2021) "Few-Shot Lifelong Learning", Proceedings of the AAAI Conference on Artificial Intelligence, p.2337-2345

Pratik Mazumder||Pravendra Singh||Piyush Rai, "Few-Shot Lifelong Learning", AAAI, p.2337-2345, 2021.

Pratik Mazumder||Pravendra Singh||Piyush Rai. "Few-Shot Lifelong Learning". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.2337-2345.

Pratik Mazumder||Pravendra Singh||Piyush Rai. "Few-Shot Lifelong Learning". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 2337-2345.

Pratik Mazumder||Pravendra Singh||Piyush Rai. Few-Shot Lifelong Learning. AAAI[Internet]. 2021[cited 2023]; 2337-2345.


ISSN: 2374-3468


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