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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 8: AAAI-21 Technical Tracks 8

SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

February 1, 2023

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Authors

Hao-Zhe Feng

Zhejiang University


Kezhi Kong

University of Maryland, College Park


Minghao Chen

Zhejiang University


Tianye Zhang

Zhejiang University


Minfeng Zhu

Zhejiang University


Wei Chen

Zhejiang University


DOI:

10.1609/aaai.v35i8.16909


Abstract:

Semi-supervised variational autoencoders (VAEs) have obtained strong results, but have also encountered the challenge that good ELBO values do not always imply accurate inference results.In this paper, we investigate and propose two causes of this problem: (1) The ELBO objective cannot utilize the label information directly. (2) A bottleneck value exists, and continuing to optimize ELBO after this value will not improve inference accuracy. On the basis of the experiment results, we propose SHOT-VAE to address these problems without introducing additional prior knowledge. The SHOT-VAE offers two contributions: (1) A new ELBO approximation named smooth-ELBO that integrates the label predictive loss into ELBO. (2) An approximation based on optimal interpolation that breaks the ELBO value bottleneck by reducing the margin between ELBO and the data likelihood. The SHOT-VAE achieves good performance with 25.30% error rate on CIFAR-100 with 10k labels and reduces the error rate to 6.11% on CIFAR-10 with 4k labels.

Topics: AAAI

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HOW TO CITE:

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations Proceedings of the AAAI Conference on Artificial Intelligence (2021) 7413-7421.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations AAAI 2021, 7413-7421.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen (2021). SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations. Proceedings of the AAAI Conference on Artificial Intelligence, 7413-7421.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen. SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.7413-7421.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen. 2021. SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations. "Proceedings of the AAAI Conference on Artificial Intelligence". 7413-7421.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen. (2021) "SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations", Proceedings of the AAAI Conference on Artificial Intelligence, p.7413-7421

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen, "SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations", AAAI, p.7413-7421, 2021.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen. "SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.7413-7421.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen. "SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 7413-7421.

Hao-Zhe Feng||Kezhi Kong||Minghao Chen||Tianye Zhang||Minfeng Zhu||Wei Chen. SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations. AAAI[Internet]. 2021[cited 2023]; 7413-7421.


ISSN: 2374-3468


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