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Video
Stanford Electrical Engineering Course on Convex Optimization.
 Course related:
 AMA4850 Optimization Methods
 Subjects:
 Mathematics and Statistics
 Keywords:
 Mathematical optimization Convex functions
 Resource Type:
 Video

Others
Linear programming, mathematical modeling technique in which a linear function is maximized or minimized when subjected to various constraints. This technique has been useful for guiding quantitative decisions in business planning, in industrial engineering, and—to a lesser extent—in the social and physical sciences.
 Course related:
 AAE3009 Operations Research and Computational Analytics in Air Transport Operations
 Subjects:
 Mathematics and Statistics
 Keywords:
 Linear programming
 Resource Type:
 Others

Courseware
This course has been designed for independent study. It provides everything you will need to understand the concepts covered in the course. The materials include:
A complete set of Lecture Videos by Professor Gilbert Strang.
Summary Notes for all videos along with suggested readings in Prof. Strang’s textbook Linear Algebra.
Problem Solving Videos on every topic taught by an experienced MIT Recitation Instructor.
Problem Sets to do on your own with Solutions to check your answers against when you’re done.
A selection of Java® Demonstrations to illustrate key concepts.
A full set of Exams with Solutions, including review material to help you prepare.
 Course related:
 AMA1120 Basic Mathematics II
 Subjects:
 Mathematics and Statistics
 Keywords:
 Algebras Linear
 Resource Type:
 Courseware

Video
With calculus well behind us, it's time to enter the next major topic in any study of mathematics. Linear Algebra! The name doesn't sound very intimidating, but there are some pretty abstract concepts in this subject. Let's start nice and easy simply by learning about what this subject covers and some basic terminology.
 Course related:
 COMP4434 Big Data Analytics
 Subjects:
 Mathematics and Statistics
 Keywords:
 Algebras Linear
 Resource Type:
 Video

Others
In these comprehensive video courses, created by Santiago Basulto, you will learn the whole process of data analysis. You'll be reading data from multiple sources (CSV, SQL, Excel), process that data using NumPy and Pandas, and visualize it using Matplotlib and Seaborn, Additionally, we've included a thorough Jupyter Notebook course, and a quick Python reference to refresh your programming skills.
 Course related:
 AMA1600 Fundamentals of AI and Data Analytics and AMA1751 Linear Algebra
 Subjects:
 Mathematics and Statistics and Computing
 Keywords:
 Computer programming Computer science Python (Computer program language)
 Resource Type:
 Others

Others
We offer mathematics in an enjoyable and easytolearn manner, because we believe that mathematics is fun.
 Subjects:
 Mathematics and Statistics
 Keywords:
 Mathematics
 Resource Type:
 Others

Video
Lecture videos from Gilbert Strang's course on Linear Algebra at MIT.
 Course related:
 AMA1120 Basic Mathematics II  Calculus and Linear Algebra
 Subjects:
 Mathematics and Statistics
 Keywords:
 Algebras Linear
 Resource Type:
 Video

Video
This course is an introduction to game theory and strategic thinking. Ideas such as dominance, backward induction, Nash equilibrium, evolutionary stability, commitment, credibility, asymmetric information, adverse selection, and signaling are discussed and applied to games played in class and to examples drawn from economics, politics, the movies, and elsewhere.
 Subjects:
 Mathematics and Statistics and Economics
 Keywords:
 Game theory
 Resource Type:
 Video

Video
Before the advent of computers around 1950, optimization centered either on smalldimensional problems solved by looking at zeroes of first derivatives and signs of second derivatives, or on infinitedimensional problems about curves and surfaces. In both cases, "variations" were employed to understand how a local solution might be characterized. Computers changed the picture by opening the possibility of solving largescale problems involving inequalities, instead of only equations. Inequalities had to be recognized as important because the decisions to be optimized were constrained by the need to respect many upper or lower bounds on their feasibility. A new kind of mathematical analysis, beyond traditional calculus, had to be developed to address these needs. It built first on appealing to the convexity of sets and functions, but went on to amazingly broad and successful concepts of variational geometry, subgradients, subderivatives, and variational convergence beyond just that. This talk will explain these revolutionary developments and why there were essential.
Event date: 1/11/2022
Speaker: Prof. Terry Rockafellar (University of Washington)
Hosted by: Department of Applied Mathematics
 Subjects:
 Mathematics and Statistics
 Keywords:
 Convex functions Convex sets Mathematical optimization Computer science  Mathematics
 Resource Type:
 Video

Video
Adaptive computation is of great importance in numerical simulations. The ideas for adaptive computations can be dated back to adaptive finite element methods in 1970s. In this talk, we shall first review some recent development for adaptive methods with some application. Then, we will propose a deep adaptive sampling method for solving PDEs where deep neural networks are utilized to approximate the solutions. In particular, we propose the failure informed PINNs (FIPINNs), which can adaptively refine the training set with the goal of reducing the failure probability. Compared with the neural network approximation obtained with uniformly distributed collocation points, the proposed algorithms can significantly improve the accuracy, especially for low regularity and highdimensional problems.
Event date: 18/10/2022
Speaker: Prof. Tao Tang (Beijing Normal UniversityHong Kong Baptist University United International College)
Hosted by: Department of Applied Mathematics
 Subjects:
 Mathematics and Statistics
 Keywords:
 Sampling (Statistics) Differential equations Partial  Numerical solutions Mathematical models Adaptive computing systems
 Resource Type:
 Video