Approximation algorithms for the TSP endeavour to provide efficient, near‐optimal solutions where exact methods prove computationally prohibitive.

Learn what approximation algorithms are, how they work, and what are some examples and challenges in computer engineering.

Geometric Optimization and Approximation Algorithms Publication Trend The graph below shows the total number of publications each year in Geometric Optimization and Approximation Algorithms.

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Approximation-Algorithms This repository is dedicated to exploring the world of approximation algorithms and their implementation in multiple programming languages. It covers a wide range of ...

Faster Algorithms via Approximation Theory illustrates how classical and modern techniques from approximation theory play a crucial role in obtaining results that are relevant to the emerging theory ...

Such algorithms find approximate (slightly suboptimal) solutions to optimization problems in polynomial time. Unlike heuristics, approximation algorithms have provable performance guarantees: they ...

Training a one-node neural network with the ReLU activation function via optimization, which we refer to as the ON-ReLU problem, is a fundamental problem in machine learning. In this paper, we begin ...

We will show how this approach can be applied in the design and analysis of primal-dual approximation algorithms. We will present several recent approximation results along these lines, starting with ...