Dynamic equations on time scales
An introductory presentation on dynamic equations on time scales and uniqueness of solutions including new research resutls. The basic ideas of time scale calculus are presented and then a new theorem is discussed under which general initial value problems have, at most, one solution. T
From playlist Mathematical analysis and applications
(ML 14.6) Forward-Backward algorithm for HMMs
The Forward-Backward algorithm for a hidden Markov model (HMM). How the Forward algorithm and Backward algorithm work together. Discussion of applications (inference, parameter estimation, sampling from the posterior, etc.).
From playlist Machine Learning
5 Simple Steps for Solving Dynamic Programming Problems
In this video, we go over five steps that you can use as a framework to solve dynamic programming problems. You will see how these steps are applied to two specific dynamic programming problems: the longest increasing subsequence problem and optimal box stacking. The five steps in order ar
From playlist Problem Solving
Dynamic Programming 1 [Programming Competition Problems]
Source code: http://problemvault.com/index.php#problem127 Problem source / Online judge: https://open.kattis.com/problems/knapsack This video explores a classic dynamic programming problem known as the "0/1 Knapsack Problem". We walk through how the algorithm works, then we go ahead and i
From playlist Programming Competition Problems with Micah Stairs
Open Middle: Systems of Equations Problem (1)
New introductory Open Middle systems of equations exercise: Using digits -9 to 9 no more than one time each, fill in the blanks to create a system of equations with given solution: https://www.geogebra.org/m/cseprgh7 #GeoGebra
From playlist Algebra 1: Dynamic Interactives!
C32 Example problem using variation of parameters
Another example problem using the method of variation of parameters.
From playlist Differential Equations
0/1 Knapsack problem | Dynamic Programming
Overview of the 0/1 Knapsack problem using dynamic programming Algorithms repository: https://github.com/williamfiset/algorithms My website: http://www.williamfiset.com
From playlist Dynamic Programming
Dynamic Graph Algorithms and Their Implementation
Abstract: While many algorithmic graph problems have been solved for static graphs, graphs that are used as models in various applications often change dynamically and, thus, require algorithms that can adapt quickly to the deletion and insertion of edges. I will start with providing an ov
From playlist SIAG-ACDA Online Seminar Series
Chiara Cammarota: "High-dimensional cost landscape and gradient descent in Tensor PCA and its ge..."
Machine Learning for Physics and the Physics of Learning 2019 Workshop IV: Using Physical Insights for Machine Learning "High-dimensional cost landscape and gradient descent in Tensor PCA and its generalisations" Chiara Cammarota - King's College London Abstract: Tensor PCA is a prototy
From playlist Machine Learning for Physics and the Physics of Learning 2019
Mirrored Langevin Dynamics - Ya-Ping Hsieh
The workshop aims at bringing together researchers working on the theoretical foundations of learning, with an emphasis on methods at the intersection of statistics, probability and optimization. We consider the posterior sampling problem in constrained distributions, such as the Latent
From playlist The Interplay between Statistics and Optimization in Learning
Andrew Childs - Efficient quantum algorithm for dissipative nonlinear differential equations
Recorded 24 January 2022. Andrew Childs of the University of Maryland presents "Efficient quantum algorithm for dissipative nonlinear differential equations" at IPAM's Quantum Numerical Linear Algebra Workshop. Abstract: While there has been extensive previous work on efficient quantum alg
From playlist Quantum Numerical Linear Algebra - Jan. 24 - 27, 2022
Lecture 19: Dynamic Programming I: Fibonacci, Shortest Paths
MIT 6.006 Introduction to Algorithms, Fall 2011 View the complete course: http://ocw.mit.edu/6-006F11 Instructor: Erik Demaine License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.006 Introduction to Algorithms, Fall 2011
Lecture 19 | Machine Learning (Stanford)
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on the debugging process, linear quadratic regulation, Kalmer filters, and linear quadratic Gaussian in the context of reinforcement learning. This course pr
From playlist Lecture Collection | Machine Learning
Using Multipliers to Solve a System of Equations Using Elimination
👉Learn how to solve a system (of equations) by elimination. A system of equations is a set of equations which are collectively satisfied by one solution of the variables. The elimination method of solving a system of equations involves making the coefficient of one of the variables to be e
From playlist Solve a System of Equations Using Elimination | Hard
Lightning Talks - Galen Cho, Christina Yu, Cyril Zhang, Laura Balzano, Max Simchovitz
Workshop on New Directions in Reinforcement Learning and Control Topic: Lightning Talks Speaker: Galen Cho, Christina Yu, Cyril Zhang, Laura Balzano, Max Simchovitz Date: November 7, 2019 For more video please visit http://video.ias.edu
From playlist Mathematics
15. Dynamic Programming, Part 1: SRTBOT, Fib, DAGs, Bowling
MIT 6.006 Introduction to Algorithms, Spring 2020 Instructor: Erik Demaine View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY This is the first of four lectures on dynamic programing. This begin
From playlist MIT 6.006 Introduction to Algorithms, Spring 2020
Lecture 14 | MIT 6.832 Underactuated Robotics, Spring 2009
Lecture 14: Feasible motion planning Instructor: Russell Tedrake See the complete course at: http://ocw.mit.edu/6-832s09 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.832 Underactuated Robotics, Spring 2009
Dynamic Programming Crash Course | Advanced Data Structures And Algorithms Tutorial | Simplilearn
🔥Post Graduate Program In Full Stack Web Development: https://www.simplilearn.com/pgp-full-stack-web-development-certification-training-course?utm_campaign=DynamicProgrammingCrashCourse-xZKqH7ZcS_Y&utm_medium=DescriptionFF&utm_source=youtube 🔥Caltech Coding Bootcamp (US Only): https://www.
From playlist Data Structures & Algorithms [2022 Updated]
What Is Dynamic Programming and How To Use It
**Dynamic Programming Tutorial** This is a quick introduction to dynamic programming and how to use it. I'm going to use the Fibonacci sequence as the primary example. Sample code is available in Jupyter Notebook and plain Python at: https://www.csdojo.io/dpcode Keep in touch on Facebook
From playlist Dynamic Programming Tutorial Series