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@@ -8,6 +8,35 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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For detailed release notes, see [GitHub Releases](https://github.com/SimonBlanke/Gradient-Free-Optimizers/releases).
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## [Unreleased]
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<!-- changelog-cursor: 466b721 -->
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### Added
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- C extension backend (`_fast_ops`) as an intermediate performance tier between numpy and pure Python, accelerating elementwise arithmetic, math functions, reductions, and matrix multiply
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-`SearchParams` dict subclass carrying optimization metadata as private attributes for tooling integration
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### Changed
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- SciPy moved from core dependency to optional extra (`pip install gradient-free-optimizers[scipy]`)
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- All optimizers ported from direct numpy imports to the internal array/math backends, enabling numpy-free operation
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- All pandas imports made lazy, reducing startup cost
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- Bayesian Optimization normalizes inputs to [0, 1] before GP fitting for better length-scale stability
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- GPR surrogate switched from Matern ν=0.5 to ν=2.5 with hyperparameter optimization (`n_restarts_optimizer=3`)
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- TPE bandwidth selection changed from hardcoded 1.0 to Silverman's rule
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- Performance improvements in GPR kernel and KDE score computation via vectorized distance matrices
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