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cs.AI2021
Exploiting a Zoo of Checkpoints for Unseen Tasks
Jiaji Huang, Qiang Qiu, Kenneth Church
There are so many models in the literature that it is difficult for practitioners to decide which combinations are likely to be effective for a new task. This paper attempts to add…
cs.LG2021
TESSERACT: Gradient Flip Score to Secure Federated Learning Against Model Poisoning Attacks
Atul Sharma, Wei Chen, Joshua Zhao +3
Federated learning---multi-party, distributed learning in a decentralized environment---is vulnerable to model poisoning attacks, even more so than centralized learning approaches.…
cs.CV2021
Adaptive Convolutions with Per-pixel Dynamic Filter Atom
Ze Wang, Zichen Miao, Jun Hu +1
Applying feature dependent network weights have been proved to be effective in many fields. However, in practice, restricted by the enormous size of model parameters and memory foo…