High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

ABSTRACT: Purpose: This study describes a machine-learning approach utilizing patients' anatomical changes to predict parotid mean dose changes in fractionated radiotherapy for head-and-neck cancer, ...

Abstract: The edit distance (also known as Levenshtein distance) of two strings is the minimum number of insertions, deletions, and substitutions of characters needed to transform one string into the ...

Script for calculating the edit distance between two strings. We compare two approaches in terms of computational time: linear storage and quadratic storage. Python scripts used to calculate 3 basic ...

This repo contains different university projects made by me, Alessio Mana and Fabrizio Sanino for our Algorithm and Data Structure Exam done in Turin in June 2021.

Abstract: The edit distance is a way of quantifying how similar two strings are to one another by counting the minimum number of character insertions, deletions, and substitutions required to ...

These days genomic sequence analysis provides a key way of understanding the biology of an organism. However, since these sequences contain much private information, it can be very dangerous to reveal ...