ISYE 6644 Week 2 Notes: Simulation
& Math Concepts Overview
Questions & Answers Rated A+ New
Update Assured Satisfaction
ISYE 6644 Simulation, Math Bootcamp
Liuyi Ye
1. Calculus
Some useful formula and properties
,
,Second derivative
2. Formal ways to search solutions to equations (finding a 0)
Bisection. By the Intermediate Value Theorem.
Newton’s method,
, It is worth noting that we use gradient descent
more in ML algorithms.
A comparison can be found here (Gatech ISYE 6416
Computational Statistics, Lecture 4, Newton’s
method and Gradient descent).
The basic idea is that:
Gradient descent tries to find a minimum x by using
information from the first derivative of the function.
Newton's method tries to find a point x satisfying
f'(x) = 0 by approximating f' with a linear function g
and then solving for the root of that function
explicitly.
3. Integration
Some useful integrals s to remember
& Math Concepts Overview
Questions & Answers Rated A+ New
Update Assured Satisfaction
ISYE 6644 Simulation, Math Bootcamp
Liuyi Ye
1. Calculus
Some useful formula and properties
,
,Second derivative
2. Formal ways to search solutions to equations (finding a 0)
Bisection. By the Intermediate Value Theorem.
Newton’s method,
, It is worth noting that we use gradient descent
more in ML algorithms.
A comparison can be found here (Gatech ISYE 6416
Computational Statistics, Lecture 4, Newton’s
method and Gradient descent).
The basic idea is that:
Gradient descent tries to find a minimum x by using
information from the first derivative of the function.
Newton's method tries to find a point x satisfying
f'(x) = 0 by approximating f' with a linear function g
and then solving for the root of that function
explicitly.
3. Integration
Some useful integrals s to remember
