Series acceleration

Related lectures (32)

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Explores error estimation in numerical integration and its applications in forecasting, emphasizing the Romberg method and Richardson extrapolation.

Explores the numerical analysis of nonlinear equations, focusing on convergence criteria and methods like bisection and fixed-point iteration.

Explains gradient descent with early stopping and stochastic gradient descent to optimize model training and prevent overfitting.

Explores Taylor series development, convergence criteria, and numerical applications.

Explores gradient descent with memory, momentum methods, conjugate gradients, and nonlinear CG on manifolds.

Explores numerical methods for solving the wave equation, discussing stability conditions and convergence rates.

Covers the convergence of Adaptive Langevin dynamics using hypocoercive techniques and explores the Central Limit Theorem.

Explores Newton's method convergence and quadratic convergence properties in theorem 8.4.

Explores accelerating the Value Iteration algorithm using control theory and matrix splitting techniques to achieve faster convergence.

Explains Lagrange interpolation for numerical integration and introduces Simpson's rules.