Computational complexity of matrix multiplication

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (30)

Page 2 of 3

Matrix Multiplication: Divide-and-Conquer

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

Column Subset Selection: RRQR and TCS

Explores RRQR, TCS, tradeoffs, accuracy metrics, and low-rank matrix factorization frameworks, emphasizing communication avoidance and recent developments.

O-Notation, Local Extrema

Covers O-Notation, local extrema, and critical points in functions.

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.

Dynamic Programming: Matrix-chain Multiplication

Explores dynamic programming with a focus on matrix-chain multiplication and the importance of optimal substructure.

Matrix Chain Multiplication

Delves into dynamic programming with a focus on Matrix Chain Multiplication and the longest common subsequence problem.

Matrix Multiplication: Algorithms and Complexity

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

Multiplications of vectors and matrices

Covers the multiplication of vectors and matrices using MATLAB and Octave for beginners.

Matrix Multiplication and Heap Data Structure

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

Gauss Representation

Explores the Gauss representation of complex numbers, focusing on addition, multiplication, bases, and vector space dimensions.