Abstract: Given a multiset of n positive integers and a target sum S, the subset sum problem is to find a subset such that the sum of its elements is as close as possible to S without exceeding S. We ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

SubsetSumSolver is a high-performance C++ tool for solving the Subset Sum Problem. It features multiple algorithms, benchmarking capabilities, and the ability to save results to a PostgreSQL database.

ABSTRACT: In agriculture sector, machine learning has been widely used by researchers for crop yield prediction. However, it is quite difficult to identify the most critical features from a dataset.

ABSTRACT: Grover’s algorithm is a category of quantum algorithms that can be applied to many problems through the exploitation of quantum parallelism. The Amplitude Amplification in Grover’s algorithm ...

A Python Implemented Cryptographic Algorithm Which Utilizes Public, Private Key Cryptography to Provide Congruent Super-Increasing Sets for Encryption of Data. This Algorithm relies on the SUBSET-SUM ...

In seeking out an algorithm to test out the capability of the IBM Quantum Experience quantum computer, we were given a review paper covering various algorithms for solving the subset-sum problem, ...

Abstract: DNA computing is a new emerging field of parallel computing. However, DNA computing is mainly based on biological technology, which is prone to deterioration and damage and other issues in ...