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This paper explains the generalization power of a deep neural network (DNN) from the perspective of interactions.
Stiffness: A new perspective on generalization in neural networks
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A simplified bargaining model for the n-person cooperative game
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Occam’s razor
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Gradient-based learning applied to document recognition
LeCun, Y.; Bottou, L.; Bengio, Y.; and Haffner, P. 1998 · 1998
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UCI machine learning repository
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Learning multiple layers of features from tiny images
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Very deep convolutional networks for large-scale image recognition
Simonyan, K.; and Zisserman, A. 2014 · 2014
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Norm-based capacity control in neural networks
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Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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On large-batch training for deep learning: Generalization gap and sharp minima
Keskar, N. S.; Mudigere, D.; Nocedal, J.; Smelyanskiy, M.; and Tang, P. T. P. 2016 · 2016
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Real time image saliency for black box classifiers
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Towards Deep Learning Models Resistant to Adversarial Attacks
DISCOVERING AND EXPLAINING THE REPRESENTATION BOTTLENECK OF DNNS
Deng, H.; Ren, Q.; Zhang, H.; and Zhang, Q. 2021 · 2021
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Toward better generalization bounds with locally elastic stability
Deng, Z.; He, H.; and Su, W. 2021 · 2021
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Sharpness-aware minimization for efficiently improving generalization
Foret, P.; Kleiner, A.; Mobahi, H.; and Neyshabur, B. 2021 · 2021
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Towards a unified information-theoretic framework for generalization
Haghifam, M.; Dziugaite, G. K.; Moran, S.; and Roy, D. 2021 · 2021
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Asam: Adaptive sharpness-aware minimization for scale-invariant learning of deep neural networks
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From noisy prediction to true label: Noisy prediction calibration via generative model
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Evaluating the robustness of neural networks: An extreme value theory approach
Weng, T.-W.; Zhang, H.; Chen, P.-Y.; Yi, J.; Su, D.; Gao, Y.; Hsieh, C.-J.; and Daniel, L. 2018 · 2018
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Explaining deep neural networks with a polynomial time algorithm for shapley value approximation
Ancona, M.; Oztireli, C.; and Gross, M. 2019 · 2019
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Sharper bounds for uniformly stable algorithms
Bousquet, O.; Klochkov, Y.; and Zhivotovskiy, N. 2020 · 2020
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Sharpened generalization bounds based on conditional mutual information and an application to noisy, iterative algorithms
Haghifam, M.; Negrea, J.; Khisti, A.; Roy, D. M.; and Dziugaite, G. K. 2020 · 2020
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A game-theoretic taxonomy of visual concepts in dnns
Cheng, X.; Chu, C.; Zheng, Y.; Ren, J.; and Zhang, Q. 2021a
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A hypothesis for the aesthetic appreciation in neural networks
Cheng, X.; Wang, X.; Xue, H.; Liang, Z.; and Zhang, Q. 2021b
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Bae, H.; Shin, S.; Na, B.; Jang, J.; Song, K.; and Moon, I.-C. 2022 · 2022
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Does a Neural Network Really Encode Symbolic Concept?
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Defining and Quantifying the Emergence of Sparse Concepts in DNNs
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Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models
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