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Related Questions
- What are some common methods for generating synthetic data to improve model robustness?
- How can we ensure that the generated synthetic data is diverse and representative of real-world scenarios?
- What is the role of anomaly detection in improving model robustness to out-of-distribution data?
- Can you explain the concept of adversarial training and its relation to synthetic data?
- How can we balance the trade-off between improving model robustness and reducing overfitting to the synthetic data?
- What are some applications of synthetic data in real-world scenarios, such as image classification or natural language processing?
- How can we evaluate the effectiveness of synthetic data in improving model robustness?
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