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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
Short description of portfolio item number 1
Short description of portfolio item number 2
publications
, 1900 [paper]
Headless Horseman: Adversarial Attacks on Transfer Learning Models.
A. Abdelkader, M. Curry, L. Fowl, T. Goldstein, A. Schwarzschild, M. Shu , C. Studer, C. Zhu, ICASSP, 2020
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 [paper]
Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer.
C. Zhu, Z. Xu, A. Shafahi, M. Shu , A. Ghiasi, and T. Goldstein, SNN (Workshop), 2021
Sparsity in Neural Networks (SNN) Workshop, 2021 [paper]
Adversarial Differentiable Data Augmentation for Autonomous Systems
M. Shu , Y. Shen, M. Lin, and T. Goldstein, ICRA, 2021
International Conferences on Robotics and Automation (ICRA), 2021 [paper] [code]
Gradient-Free Adversarial Training against Image Corruption for Learning-based Steering
Y. Shen, L. Zheng, M. Shu , W. Li, T. Goldstein and M. Lin, NeurIPS, 2021
Conference on Neural Information Processing Systems (NeurIPS), 2021 [paper] [code]
Encoding Robustness to Image Style via Adversarial Feature Perturbations
M. Shu , Z. Wu, M. Goldblum, and T. Goldstein, NeurIPS, 2021
Conference on Neural Information Processing Systems (NeurIPS), 2021 [paper] [code]
The Close Relationship between Contrastive Learning and Meta Learning
R. Ni*, M. Shu*, H. Souri, M. Goldblum, and T. Goldstein, ICLR, 2022
International Conferences on Learning Representations (ICLR), 2022 [paper] [code]
Where do models go wrong? Parameter-space saliency maps for explainability.
R. Levin*, M. Shu*, E. Borgnia*, F. Huang, M. Goldblum, T. Goldstein, NeurIPS, 2022
Conference on Neural Information Processing Systems (NeurIPS), 2022 [paper]
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models
M. Shu , W. Nie, DA. Huang, Z. Yu, T. Goldstein, A. Anandkumar, and C. Xiao, NeurIPS, 2022
Conference on Neural Information Processing Systems (NeurIPS), 2022 [paper] [code]
talks
Conference Proceeding talk 3 on Relevant Topic in Your Field
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