Proceedings of the Workshop on Artificial Intelligence Safety 2020 co-located with the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020), 2020

Rethinking Softmax Cross-Entropy Loss for Adversarial Robustness.

[BibT_eX]

[DOI]

Tianyu Pang

Proceedings of the 8th International Conference on Learning Representations, 2020

Benchmarking Adversarial Robustness on Image Classification.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Stochastic Quantization for Learning Accurate Low-Bit Deep Neural Networks.

[BibT_eX]

[DOI]

Int. J. Comput. Vis., 2019

Benchmarking Adversarial Robustness.

[BibT_eX]

[DOI]

CoRR, 2019

Improving Black-box Adversarial Attacks with a Transfer-based Prior.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficient Decision-Based Black-Box Adversarial Attacks on Face Recognition.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Composite Binary Decomposition Networks.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Adversarial Attacks and Defences Competition.

[BibT_eX]

[DOI]

CoRR, 2018

Towards Robust Detection of Adversarial Examples.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Visual Knowledge Memory Networks for Visual Question Answering.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Defense Against Adversarial Attacks Using High-Level Representation Guided Denoiser.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Boosting Adversarial Attacks With Momentum.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Discovering Adversarial Examples with Momentum.

[BibT_eX]

[DOI]

CoRR, 2017

Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples.

[BibT_eX]

[DOI]

CoRR, 2017

Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization.

[BibT_eX]

[DOI]

CoRR, 2017

Forecast the Plausible Paths in Crowd Scenes.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Improving Interpretability of Deep Neural Networks with Semantic Information.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization.

[BibT_eX]

[DOI]

Yinpeng Dong

Jianguo Li

Renkun Ni

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Feature Engineering and Ensemble Modeling for Paper Acceptance Rank Prediction.

[BibT_eX]

[DOI]

CoRR, 2016

Crowd Scene Understanding with Coherent Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Efficient and Robust Semi-supervised Learning Over a Sparse-Regularized Graph.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2016, 2016

Yinpeng Dong

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