Lectures related to Matrix multiplication algorithm

Matrix-Matrix Multiplication: Algorithms and Applications

Explores theoretical and practical aspects of fast matrix-matrix multiplication algorithms and their significance in computer science.

Matrix Multiplication and Divide-and-Conquer Techniques

Discusses matrix multiplication using divide-and-conquer techniques and introduces Strassen's algorithm for improved efficiency.

Matrix Multiplication: Strassen's Algorithm

Introduces matrix multiplication and Strassen's algorithm, covering divide-and-conquer approach, data structures like heaps, and MAX-HEAPIFY operation.

Matrix Multiplication

Covers matrix multiplication, properties, and the identity matrix in algebraic operations.

Dynamic Programming: Matrix Chain Multiplication

Explores dynamic programming with a focus on optimizing Matrix Chain Multiplication.

Matrix Chain Multiplication: Optimal Substructure and Recursive Formula

Explores optimal substructure and recursive formula in matrix chain multiplication using dynamic programming.

Matrix Multiplication: Algorithms and Complexity

Covers matrix notation, arithmetic, multiplication algorithms, and complexity analysis.

Linear Combinations and Vector Spaces

Introduces linear combinations in vector spaces, operations, and polynomials of degree 2.

Matrix Operations: Definitions and Examples

Covers the basic operations on matrices, including addition, scalar multiplication, and matrix multiplication.

Recursion Trees and Matrix Multiplication

Covers recursion trees, the maximum subarray problem, and matrix multiplication approaches.

Matrix Multiplication: Divide-and-Conquer

Covers divide-and-conquer in matrix multiplication, recursion trees, the master method, maximum-subarray problem, and smart algorithm.

Matrix Chain Multiplication

Explores matrix chain multiplication to minimize scalar multiplications efficiently.

Linear Algebra: Matrices and Operations

Introduces key concepts in linear algebra, including matrices, operations, and numerical invariants.

Dynamic Programming: Rod Cutting and Matrix Chain Multiplication

Introduces dynamic programming with a focus on rod cutting and matrix chain multiplication.

Matrix Multiplication and Heap Data Structure

Covers the divide-and-conquer algorithm for matrix multiplication and introduces the (binary) heap data structure.

Vector Spaces: Definition, R2

Introduces vector spaces with binary addition and scalar multiplication, exploring geometric examples in R2.

Matrix Multiplication: Divide-and-Conquer

Explores the Divide-and-Conquer algorithm for matrix multiplication, including Strassen's Method and its significance in optimizing time complexity.

Principles of Parallelism

Covers the basics of parallelism, including physical examples, historical context, multicore era, and parallel collections in Scala.

Matrix Multiplication and Heaps: Efficient Algorithms

Discusses Strassen's algorithm for matrix multiplication and heaps, covering efficient algorithms and their applications in computer science.

Matrix Multiplication: Algorithms and Complexity

Covers matrix notation, arithmetic, multiplication, algorithms, and complexity of matrix multiplication.