# Efficient and Effective Augmentation Strategy for Adversarial Training

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/efficient-and-effective-augmentation-strategy-for-adversarial-training/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sravanti Addepalli,Samyak Jain,R. Venkatesh Babu |
| Citations | 11 |
| DOI | 10.48550/arxiv.2210.15318 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2210.15318 |
| OpenAlex ID | https://openalex.org/W4307539041 |
| Type | preprint |
| Year | 2022 |

## Paper authors

- [Samyak Jain](https://scholariq.org/researchers/samyak-jain/)

## Paper journal

- [arXiv (Cornell University)](https://scholariq.org/journals/arxiv-cornell-university/)

## Paper primary topic

- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)

## Paper topics

- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [Domain Adaptation and Few-Shot Learning](https://scholariq.org/topics/domain-adaptation-and-few-shot-learning/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.