executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
Skills 둘러보기
생산성 및 협업 · SKILL.md
mas_regularized_training
mas_regularized_trainingApply the MAS quadratic regularizer during later-task training and log parameter drift evidence.
Independent GitHub snapshot · Automated classification · Original documentation governs
Skill 문서
GitHubname: mas_regularized_training description: Apply the MAS quadratic regularizer during later-task training and log parameter drift evidence.
MAS Regularized Training
Use for later-task optimizer steps with task_loss + lambda * sum(Omega * (theta-theta_star)^2). Inputs are weights, task data, snapshot, importance, lambda, and optimizer settings. Outputs are updated parameters and loss/penalty traces. Validate with python tests/test_regularizer.py.