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Optimizations

Overfitting

• Overfittig - SanghyukChun blog
• Understanding the Bias-Variance Tradeoff - Fortmann-Roe Essays
• 최적화 기법의 직관적 이해 - 다크 프로그래머 blog

Convex Optimization

• Convex Optimization (Gradient Descent) - SanghyukChun blog

Non-Convex Optimization

• Identifying and attacking the saddle point problem in high-dimensional non-convex optimization - 2015 paper
• Local Minima 문제에 대한 새로운 시각 - 다크 프로그래머 blog
• Non-convex Optimization - 2017 paper

Contrained Optimization

• Contrained Optimization: Step by Step lecture note

Uncotrained Optimization

• Uncontrained Optimization lecture slide

Linear Programming

• Linear Programming book

Quadratic Programming

• Quadratic Programming book

Semidefinite Programming

• Introduction to Semidefinite Programming book

Least Square Method

• 여러가지 이름.
  • Least Mean Square
  • 최소자승법
  • 최소제곱법
• 최소자승법 이해와 다양한 활용예 (Least Square Method) - 다크 프로그래머 blog

Gradient Descent

• Gradient Descent - Texas University lecture note
• Gradient Descent - 다크프로그래머 blog
• Gradient Descent 탐색 방법 - 다크프로그래머 blog

Levenberg–Marquardt Method

• 함수최적화 기법 정리 (Levenberg–Marquardt 방법 등) - 다크 프로그래머 blog
• 대수적 에러와 기하학적 에러(Algebraic & Geometric Error) - 다크 프로그래머 (blog)[http://darkpgmr.tistory.com/143?category=761008]

ALS

• SGD vs. ALS on solving BiasedMF(SVD) - 수원혼모노이현성 blog https://ita9naiwa.github.io/recommender%20systems/2017/11/25/SGD-versus-ALS.html

Coordinat Descent

• Coordinate Descent Algorithms paper

Steepest Descent

• Method of steepest descent lecture note

Hyperparameter optimization

• Hyperparameter #1 종류 - 라온피플 blog
• Hyperparameter #2 방법 - 라온피플 blog

Bayesian optimization

• Practical Bayesian optimization of machine learning algorithms - 2012 paper
• Practical Bayesian Optimization of Machine Learning Algorithms - SanghyukChun blog ***