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Lecture 2 from UW-Madison's Summer 2022 iteration of CS 577: Introduction to Algorithms. This lecture presented the technique ...

Function Approximation, Probabilistic View Point, Deterministic View Point.

Approximation algorithm for the vertex cover problem.

Notes: https://drive.google.com/drive/folders/1gdXBCpHF6hGWMjLxu_bPg01J7NyYLle6?usp=drive_link.

In this video, we clearly explain the Vertex Cover Problem from Graph Theory — one of the most important problems in Design ...

Ever wondered how the quality of an approximation algorithm like QAOA is actually determined in quantum computing?

... computational challenges are so difficult and how we can use approximation algorithms and AI to find near-optimal solutions.

In this video, we introduce many of the basic notions of mathematical optimization — a core topic in statistics, machine learning, ...

let's learn about algorithms #algorithm #algorithmhacks #tech #coder #codelover #oops #logic.

Recording from the University of Maryland, College Park's Multi-Agent Reinforcement Learning Seminar as presented in March of ...

Title: Faster Combinatorial Algorithms for Bipartite Matching Abstract: Maximum bipartite matching is among the most fundamental ...

Please consider supporting us on Patreon if you enjoy our content: https://www.patreon.com/thesyntheticmind What's the best way ...

This lecture covers parallel programming models in C++, focusing on threads and synchronization. The numerical approximation ...

Greedy algorithms make the best local decision at each step to efficiently approximate a global solution. They are useful when ...

I will overview several practical tricks for handling (interpolating) functions efficiently, and discuss how they can help your ...

Corresponds to Section 6.5 for MATH 1000 at LCCC.

We explore the new approximation algorithms proposed (with upper bounds of 3 and 2) and discuss the novel concept of "strong ...

Delve into the core reasons why the approximation quality of QAOA (Quantum Approximate Optimization Algorithm) isn't just ...