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04/10/2023
Revisiting Test Time Adaptation under Online Evaluation
This paper proposes a novel online evaluation protocol for Test Time Ada...
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02/02/2023
Real-Time Evaluation in Online Continual Learning: A New Paradigm
Current evaluations of Continual Learning (CL) methods typically assume ...
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12/09/2022
PIVOT: Prompting for Video Continual Learning
Modern machine learning pipelines are limited due to data availability, ...
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11/29/2022
SimCS: Simulation for Online Domain-Incremental Continual Segmentation
Continual Learning is a step towards lifelong intelligence where models ...
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09/29/2022
Generalizability of Adversarial Robustness Under Distribution Shifts
Recent progress in empirical and certified robustness promises to delive...
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06/06/2022
Certified Robustness in Federated Learning
Federated learning has recently gained significant attention and popular...
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04/12/2022
3DeformRS: Certifying Spatial Deformations on Point Clouds
3D computer vision models are commonly used in security-critical applica...
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02/10/2022
Towards Assessing and Characterizing the Semantic Robustness of Face Recognition
Deep Neural Networks (DNNs) lack robustness against imperceptible pertur...
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01/31/2022
On the Robustness of Quality Measures for GANs
This work evaluates the robustness of quality measures of generative mod...
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07/29/2021
Enhancing Adversarial Robustness via Test-time Transformation Ensembling
Deep learning models are prone to being fooled by imperceptible perturba...
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07/09/2021
ANCER: Anisotropic Certification via Sample-wise Volume Maximization
Randomized smoothing has recently emerged as an effective tool that enab...
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07/02/2021
DeformRS: Certifying Input Deformations with Randomized Smoothing
Deep neural networks are vulnerable to input deformations in the form of...
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03/26/2021
Combating Adversaries with Anti-Adversaries
Deep neural networks are vulnerable to small input perturbations known a...
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12/08/2020
Data Dependent Randomized Smoothing
Randomized smoothing is a recent technique that achieves state-of-art pe...
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06/13/2020
ClustTR: Clustering Training for Robustness
This paper studies how encouraging semantically-aligned features during ...
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05/03/2020
Adaptive Learning of the Optimal Mini-Batch Size of SGD
Recent advances in the theoretical understandingof SGD (Qian et al., 201...
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02/20/2020
On the Decision Boundaries of Deep Neural Networks: A Tropical Geometry Perspective
This work tackles the problem of characterizing and understanding the de...
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12/11/2019