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Found 5 papers, 2 papers with code
Improve Sentence Alignment by Divide-and-conquer
In this paper, we introduce a divide-and-conquer algorithm to improve sentence alignment speed.
Adversarial Attack via Dual-Stage Network Erosion
Deep neural networks are vulnerable to adversarial examples, which can fool deep models by adding subtle perturbations.
Learning Coated Adversarial Camouflages for Object Detectors
An adversary can fool deep neural network object detectors by generating adversarial noises.
Gradient Episodic Memory with a Soft Constraint for Continual Learning
Catastrophic forgetting in continual learning is a common destructive phenomenon in gradient-based neural networks that learn sequential tasks, and it is much different from forgetting in humans, who can learn and accumulate knowledge throughout their whole lives.
Making Adversarial Examples More Transferable and Indistinguishable
Fast gradient sign attack series are popular methods that are used to generate adversarial examples.
