Bias-Variance Tradeoff¶

• Wiki

• MLU-Explain bias-variance

• MLU-Explain double-descent, part 1

Further Reading

• MLU-Explain double-descent, part 2

• The Bias-Variance Tradeoff: A Newbie’s Guide, by a Newbie

• bias-variance-trade-off

Paper: VC Theoretical Explanation of Double Descent

Paper: Reconciling modern machine-learning practice and the classical bias–variance trade-off

• Double Descent

• Reproducing Deep Double Descent

  • deep_double_descent, colab

• Sec 22.3 of Zaki

Paper: Understanding the double descent curve in Machine Learning

From high-dimensional into low-dimensional Euclidean space¶

• Random Projection: Theory and Implementation in Python with Scikit-Learn

• Johnson–Lindenstrauss lemma

• Gaussian random projection

• Scikit-learn: The Johnson-Lindenstrauss bound for embedding with random projections

Paper: Supervised dimensionality reduction for big data

Paper: An Introduction to Johnson–Lindenstrauss Transforms

• Sketching Algorithms for Big Data, Harvard

  • JL Lemma, History of lower bounds

  • JL Lower bound Optimality