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Found 3 papers, 2 papers with code
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization
Bilevel optimization problems, which are problems where two optimization problems are nested, have more and more applications in machine learning.
Benchopt: Reproducible, efficient and collaborative optimization benchmarks
Numerical validation is at the core of machine learning research as it allows to assess the actual impact of new methods, and to confirm the agreement between theory and practice.
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms
However, computing the gradient of the value function involves solving a linear system, which makes it difficult to derive unbiased stochastic estimates.
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