[ML] PAC-Bayes Bound : Measure for Generalization Ability of Learned Predictors

References An Introduction to PAC-Bayes User-friendly introduction to PAC-Bayes bounds, Alquier et al., 2021 PAC...

2023, Dec 06   —  1 minute read

[Convex Optimization] Solving Soft Margin SVM by Primal-Dual IPM with Kernel Tricks

1. Summary Notes provides a summary of the entire process for optimizing a soft-margin SVM....

2023, Apr 02   —  10 minute read

[Convex Optimization] Soft Marin SVM & Introduction of Kernel Tricks

Soft Margin SVM that provides flexibility by allowing some classification error by introducing some slack...

2023, Apr 02   —  1 minute read

[Convex Optimization] Support Vector Machine (SVM) with KKT Optimization

Optimization of Support Vector Machine for binary classification problem by solving dual problem for KKT...

2023, Apr 01   —  1 minute read

[Convex Optimization] Interior-Point Method with Barrier Function

Optimization algorithm commonly used to solve convex optimization problems using Newton method starts with perturbed...

2023, Mar 15   —  1 minute read

[Convex Optimization] Primal-Dual Interior-Point Method (PD-IPM)

also uses perturbed KKT as IPM-B, but doen’t explicitly uses barrier method instead, solving primal-dual...

2023, Mar 09   —  1 minute read

[Convex Optimization] Karush Kuhn Tucker (KKT) Conditions and Strong Duality

Summary Notes Convex Optimization 3 - Karush Kuhn Tucker (KKT) Conditions and Strong Duality Applications...

2023, Mar 06   —  1 minute read

[Convex Optimization] Quasi-Newton Method 1 : Broyden's Method

Quasi-Newton method Iterative optimization algorithm used to solve unconstrained nonlinear optimization problems without explicit calculation...

2023, Mar 02   —  1 minute read

[Convex Optimization] Quasi-Newton Method 2 : SR1, BFGS, DFP

SR1, BFGS, DFP SR1, BFGS, and DFP are all quasi-Newton methods that are commonly used...

2023, Mar 02   —  1 minute read