Regular biography
Casey Garner is a Research Fellow at the Mathematical Institute, University of Oxford, within the Department of Mathematics. Their research interests are currently not specified in available records. Garner's profile page indicates an affiliation with the Numerical Analysis research group. Further details regarding their academic background, achievements, and specific research areas are not provided in the available information.
Scholar-generated biography
Casey Garner is a Postdoctoral Researcher at the University of Oxford, specializing in continuous optimization and numerical analysis. Their research focuses on developing efficient algorithms for optimization problems with complex constraints, including spectral constrained matrix optimization and uncertain data envelopment analysis. Garner's work explores techniques such as Anderson acceleration, FISTA variants, and surrogate-based methods for hyperparameter optimization. They have contributed to improving convergence rates in fixed-point iterations and applying optimization techniques to parameter estimation and fairness in machine learning. Their research bridges theoretical analysis with practical applications in numerical methods and optimization.