Corpus ID: 219980366

Approximate Cross-Validation for Structured Models

@article{Ghosh2020ApproximateCF,
  title={Approximate Cross-Validation for Structured Models},
  author={S. Ghosh and William T. Stephenson and Tin D. Nguyen and Sameer K Deshpande and Tamara Broderick},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.12669}
}
Many modern data analyses benefit from explicitly modeling dependence structure in data -- such as measurements across time or space, ordered words in a sentence, or genes in a genome. Cross-validation is the gold standard to evaluate these analyses but can be prohibitively slow due to the need to re-run already-expensive learning algorithms many times. Previous work has shown approximate cross-validation (ACV) methods provide a fast and provably accurate alternative in the setting of empirical… Expand
2 Citations

Figures from this paper

References

SHOWING 1-10 OF 56 REFERENCES
Approximate Cross-Validation in High Dimensions with Guarantees
  • 6
  • PDF
Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC
  • 1,277
  • PDF
On Optimal Generalizability in Parametric Learning
  • 28
  • Highly Influential
  • PDF
Cross validation in LASSO and its acceleration
  • 26
  • PDF
A Swiss Army Infinitesimal Jackknife
  • 36
  • PDF
Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization
  • 6
  • PDF
On the Accuracy of Influence Functions for Measuring Group Effects
  • 37
  • PDF
...
1
2
3
4
5
...