Code for designing sigma delta modulator loop filters with optimal properties.
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Updated
Aug 31, 2023 - MATLAB
Code for designing sigma delta modulator loop filters with optimal properties.
The code for large margin metric learning for nearest neighbor classification and its acceleration using triplet mining and stratified sampling
An accelerated active‑set algorithm for a quadratic semidefinite program with general constraints
An Exact Solver for Cardinality-constrained Minimum Sum-of-Squares Clustering
Code for symbolic validations of the PEP-based proofs for the article " Worst-case convergence analysis of gradient and Newton methods through semidefinite programming performance estimation" authored by E. de Klerk, F. Glineur and A. Taylor
This code can be used to reproduce all results from the paper "Smooth strongly convex interpolation and exact worst-case performance of first-order methods" (published in Mathematical Programming). (newer version available in the PESTO toolbox)
Code to reproduce the results presented in the work "Efficient First-order Methods for Convex Minimization: a Constructive Approach" (in Mathematical Programming series A) by Y. Drori and A. Taylor.
Standard errors for moment matching estimators given limited knowledge about the moment variance-covariance matrix
An open-source interface to use the multiple-precision solver SDPA-GMP with YALMIP
An open-source add-on for YALMIP to solve optimisation problems with polynomial quadratic integral inequality constraints.
Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analyses of first-order methods in convex and nonconvex optimization. The numerical worst-case analyses from PEP can be performed just by writting the algorithms just as you would implement them.
LipSDP - Lipschitz Estimation for Neural Networks
Solver for Large-Scale Rank-One Semidefinite Relaxations
Bayesian Optimization of Combinatorial Structures
Certifiable Outlier-Robust Geometric Perception
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