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 ...

In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs).

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

We extend the (1 — 1/e)-approximation algorithm to a constant-factor approximation algorithms for a nonseparable assignment problem with applications in maximizing revenue for budget-constrained ...

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 ...

Michel Gendreau, Gilbert Laporte, Alain Hertz, An Approximation Algorithm for the Traveling Salesman Problem with Backhauls, Operations Research, Vol. 45, No. 4 (Jul ...

Approximation Algorithm for the NP-Complete problem of finding a vertex cover of minimum weight in a graph with weighted vertices. Guarantees an answers at most 2 times the optimal minimum weighted ...