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Paper Abstract and Keywords
Presentation 2022-02-21 13:00
Domain Incremental Leaning with Adaptive Loss Functions
Takumi Kawashima (UTokyo), Go Irie, Daiki Ikami (NTT), Kiyoharu Aizawa (UTokyo)
Abstract (in Japanese) (See Japanese page) 
(in English) During domain incremental learning of image classification task, the distribution of images continually change, and models adapt themselves to images with new features while retaining past knowledge. There are very few methods specialized in it compared to class incremental learning, where new classes are incrementally added. In this work, we propose a simple method for domain incremental learning problems. Our proposed method is based on rehearsal with exemplars, and adaptively decide weights of loss functions. In our experiments, we use three datasets, one of which we made for this task.
Keyword (in Japanese) (See Japanese page) 
(in English) image classification / deep learning / catastrophic forgetting / domain incremental learning / distillation loss / / /  
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Conference Information
Committee AIT ME MMS IEICE-IE IEICE-ITS  
Conference Date 2022-02-21 - 2022-02-22 
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Place (in English) online 
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Paper Information
Registration To IEICE-IE 
Conference Code 2022-02-IE-ITS-AIT-ME-MMS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Domain Incremental Leaning with Adaptive Loss Functions 
Sub Title (in English)  
Keyword(1) image classification  
Keyword(2) deep learning  
Keyword(3) catastrophic forgetting  
Keyword(4) domain incremental learning  
Keyword(5) distillation loss  
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1st Author's Name Takumi Kawashima  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Go Irie  
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
3rd Author's Name Daiki Ikami  
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
4th Author's Name Kiyoharu Aizawa  
4th Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2022-02-21 13:00:00 
Presentation Time 15 minutes 
Registration for IEICE-IE 
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Volume (vol) vol.46 
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