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Related Questions
- What are some common techniques for dimensionality reduction in recommendation systems?
- How can feature selection be used to reduce the curse of dimensionality?
- What is the difference between PCA and t-SNE in dimensionality reduction?
- Can you explain the concept of latent semantic analysis (LSA) and its application in recommendation systems?
- How can manifold learning techniques be used to reduce dimensionality in high-dimensional spaces?
- What are some trade-offs between dimensionality reduction techniques and their impact on recommendation system performance?
- Can you discuss the role of data preprocessing in mitigating the curse of dimensionality in recommendation systems?
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