Adaptive Regularization using Cubics for Optimization // Implements cubic regularization methods (ARC) for local optimization problems common in statistics and applied research. Provides robust handling of ill-conditioned, nonconvex, and indefinite Hessian problems with automatic saddle point escape. Supports box constraints; linear equality constraints are planned for a future release.