Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness | Paper Citation Record

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Detecting brittle decisions for free: leveraging margin consistency in deep robust classifiers , year =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of the 32nd International Conference on Neural Information Processing Systems , pages =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation , url =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness ImageNet Classification with Deep Convolutional Neural Networks , url =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Attention is All you Need , url =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Language Models are Few-Shot Learners , url =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness International Conference on Learning Representations , year=

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Algorithmic Learning Theory: 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings , pages =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness and Foster, Dylan J

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness LipsFormer: Introducing

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of the Thirtieth International Conference on Very Large Data Bases - Volume 30 , pages =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of the 41st International Conference on Machine Learning , pages =

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of the 32nd International Conference on Machine Learning , pages =

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Reference 63

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Reference 70

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Reference 73

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Reference 74

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Reference 80

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Reference 81

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Reference 82

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of the 32nd International Conference on Neural Information Processing Systems , pages =

Reference 83

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Reference 84

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of The 33rd International Conference on Machine Learning , pages =

Reference 85

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Reference 86

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Reference 87

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Reference 89

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Reference 91

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Reference 93

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of the 38th International Conference on Machine Learning , pages =

Reference 94

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Reference 96

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Reference 98

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Lipschitz Continuity in Deep Learning: A Systematic Review of Theoretical Foundations, Estimation Methods, Regularization Approaches, and Certifiable Robustness Proceedings of The 3rd Conference on Lifelong Learning Agents , pages =

Reference 99

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