Alexander Levine

Affiliations:
  • University of Texas at Austin, TX, USA
  • University of Maryland, MD, USA (former)


According to our database1, Alexander Levine authored at least 23 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
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Links

Online presence:

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Bibliography

2024
Multistep Inverse Is Not All You Need.
CoRR, 2024

2023
Scalable Methods for Robust Machine Learning.
PhD thesis, 2023

Provable Robustness against Wasserstein Distribution Shifts via Input Randomization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Goal-Conditioned Q-learning as Knowledge Distillation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Invariant Learning via Diffusion Dreamed Distribution Shifts.
CoRR, 2022

Certifying Model Accuracy under Distribution Shifts.
CoRR, 2022

Lethal Dose Conjecture on Data Poisoning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation.
Proceedings of the International Conference on Machine Learning, 2022

Policy Smoothing for Provably Robust Reinforcement Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Provable Adversarial Robustness for Fractional Lp Threat Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Improved, Deterministic Smoothing for L1 Certified Robustness.
CoRR, 2021

Improved, Deterministic Smoothing for L<sub>1</sub> Certified Robustness.
Proceedings of the 38th International Conference on Machine Learning, 2021

Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Tight Second-Order Certificates for Randomized Smoothing.
CoRR, 2020

Deep Partition Aggregation: Provable Defense against General Poisoning Attacks.
CoRR, 2020

Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Certifying Confidence via Randomized Smoothing.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

(De)Randomized Smoothing for Certifiable Defense against Patch Attacks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Curse of Dimensionality on Randomized Smoothing for Certifiable Robustness.
Proceedings of the 37th International Conference on Machine Learning, 2020

Wasserstein Smoothing: Certified Robustness against Wasserstein Adversarial Attacks.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Certifiably Robust Interpretation in Deep Learning.
CoRR, 2019


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