Results 11 to 20 of about 1,057,004 (267)
Self-Attentive Sequential Recommendation [PDF]
2018 IEEE International Conference on Data Mining (ICDM), 2018 Accepted by ICDM'18 as a long ...
Wang-Cheng Kang, Julian J. McAuley
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On The Computational Complexity of Self-Attention
CoRR, 2022 Transformer architectures have led to remarkable progress in many state-of-art applications. However, despite their successes, modern transformers rely on the self-attention mechanism, whose time- and space-complexity is quadratic in the length of the input.
Feyza Duman Keles +2 more
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Self-Reported Attention Control Skills Moderate the Effect of Self-Focused Attention on Depression
SAGE Open, 2021 This study aimed to examine whether attention control skills (selective, switching, and divided attention) moderate the influence of self-preoccupation (the tendency to maintain self-focused attention) on depression. We conducted a cross-sectional survey
Haruyuki Ishikawa, Fusako Koshikawa
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Lightweight Self-Attentive Sequential Recommendation [PDF]
Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021 Modern deep neural networks (DNNs) have greatly facilitated the development of sequential recommender systems by achieving state-of-the-art recommendation performance on various sequential recommendation tasks. Given a sequence of interacted items, existing DNN-based sequential recommenders commonly embed each item into a unique vector to support ...
Yang Li 0140 +3 more
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On the Robustness of Self-Attentive Models [PDF]
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019 This work examines the robustness of self-attentive neural networks against adversarial input perturbations. Specifically, we investigate the attention and feature extraction mechanisms of state-of-the-art recurrent neural networks and self-attentive architectures for sentiment analysis, entailment and machine translation under adversarial attacks.
Yu-Lun Hsieh +5 more
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Switchable Self-attention Module
CoRR, 2022 Attention mechanism has gained great success in vision recognition. Many works are devoted to improving the effectiveness of attention mechanism, which finely design the structure of the attention operator. These works need lots of experiments to pick out the optimal settings when scenarios change, which consumes a lot of time and computational ...
ShanShan Zhong, Wushao Wen, Jinghui Qin
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Self-reported interoceptive accuracy and interoceptive attention differentially correspond to measures of visual attention and self-regard [PDF]
PeerJ, 2023 Background Interoception, the perception of bodily functions and sensations, is a crucial contributor to cognition, emotion, and well-being. However, the relationship between these three processes is not well understood. Further, it is increasingly clear
Erik M. Benau
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On the Integration of Self-Attention and Convolution
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Accepted to ...
Xuran Pan +6 more
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Exploring Self-Attention for Image Recognition [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 CVPR 2020, Code available at https://github.com/hszhao ...
Hengshuang Zhao +2 more
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Adaptive aggregation with selfâattention network for gastrointestinal image classification
IET Image Processing, 2022 Automatic classification of diseases in endoscopic images is essential to the improvement of diagnostic performance and the reduction of colorectal cancer mortality.
Sheng Li +5 more
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