Klas Leino

According to our database, Klas Leino authored at least 20 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Recipe for Improved Certifiable Robustness.

Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Is Certifying 𝓁_p Robustness Still Worthwhile?

Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu, Weicheng Yu, Corina S. Pasareanu, Anupam Datta, Matt Fredrikson

CoRR, 2023

A Recipe for Improved Certifiable Robustness: Capacity and Data.

Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson

CoRR, 2023

Scaling in Depth: Unlocking Robustness Certification on ImageNet.

Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson

CoRR, 2023

Limitations of Piecewise Linearity for Efficient Robustness Certification.

Klas Leino

CoRR, 2023

Unlocking Deterministic Robustness Certification on ImageNet.

Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Perils of Cascading Robust Classifiers.

Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Degradation Attacks on Certifiably Robust Neural Networks.

Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu

Trans. Mach. Learn. Res., 2022

Selective Ensembles for Consistent Predictions.

Emily Black, Klas Leino, Matt Fredrikson

Proceedings of the Tenth International Conference on Learning Representations, 2022

Self-correcting Neural Networks for Safe Classification.

Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu

Proceedings of the Software Verification and Formal Methods for ML-Enabled Autonomous Systems, 2022

2021

Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair.

Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu

CoRR, 2021

Relaxing Local Robustness.

Klas Leino, Matt Fredrikson

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exploring Conceptual Soundness with TruLens.

Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Ricardo Shih, Zifan Wang

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Machine Learning Explainability and Robustness: Connected at the Hip.

Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Zifan Wang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Globally-Robust Neural Networks.

Klas Leino, Zifan Wang, Matt Fredrikson

Proceedings of the 38th International Conference on Machine Learning, 2021

Fast Geometric Projections for Local Robustness Certification.

Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference.

Klas Leino, Matt Fredrikson

Proceedings of the 29th USENIX Security Symposium, 2020

Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models.

Kaiji Lu, Piotr Mardziel, Klas Leino, Matt Fredrikson, Anupam Datta

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Feature-Wise Bias Amplification.

Klas Leino, Emily Black, Matt Fredrikson, Shayak Sen, Anupam Datta

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Influence-Directed Explanations for Deep Convolutional Networks.

Klas Leino, Shayak Sen, Anupam Datta, Matt Fredrikson, Linyi Li

Proceedings of the IEEE International Test Conference, 2018