Continuous Optimization for Data Science (317 Pages) by Moshe Haviv

Author:Moshe Haviv
Format: pdf
Tags: Convex Sets, Convex Functions, Concave Functions, Maximum Likelihood Estimators, MLE, First Order Condition, Second Order Condition, Curve Fitting, Newton's Method, False Position Method, Rate of Convergence, Quadratic Fitting, Cubic Fitting, Unimodal Function, Fibonacci Search, Unconstrained Optimization, Line Search, Local Minimum, Local Maximum, Least Squares, Linear Regression, Logistic Regression, Linear Neural Networks, Steepest Descent, Gradient Descent, Quasi-Newton, Expectation-maximization Algorithm, Constrained Optimization, Allocation Problems, Linear Constrains, Linear Programming, Lagrange Multipliers, Dual Variables, Best Linear Unbiased Estimator, Shadow Price, Duality, Non-linear Programming, Quadratic Programming, KKT, Karush–Kuhn–tacker, Convex Programming, Support Vector Machine, Lagrangian Method, Penalty Functions, Barrier Functions, Simplex, Feasible Solution, Transportation Problem, Representation Theorem, Sensitivity Analysis
Published: 2025-06-04T10:07:33+00:00


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