CVCRFeb 1, 2019

Adaptive Gradient for Adversarial Perturbations Generation

arXiv:1902.01220v611 citations
Originality Synthesis-oriented
AI Analysis

This tackles adversarial robustness in machine learning, but appears incremental as it builds on existing gradient-based methods.

The paper addresses the problem of generating adversarial perturbations for deep neural networks, but the abstract does not provide specific results or numbers.

Deep Neural Networks have achieved remarkable success in computer vision, natural language processing, and audio tasks.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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