| # Repro - Provably Data-driven Multiple Hyper-parameter Tuning with Structured Loss Function | |
| ## Pages | |
| | Page | | |
| | --- | | |
| | [Claim 1: Establishes first general framework for generalization guarantees for multi-dimensional hyperparameter tuning](#/claim-1-establishes-first-general-framework-for-generalization-guarantees-for-multi-dimensional-hyperparameter-tuning) | | |
| | [Claim 2: Strengthens guarantees using semi-algebraic function classes with finite fat-shattering dimension](#/claim-2-strengthens-guarantees-using-semi-algebraic-function-classes-with-finite-fat-shattering-dimension) | | |
| | [Claim 3: Derives improved bounds for data-driven weighted group lasso and weighted fused lasso](#/claim-3-derives-improved-bounds-for-data-driven-weighted-group-lasso-and-weighted-fused-lasso) | | |
| | [Conclusion](#/conclusion) | | |