D

dynamic-programming

Python research code for segment-based change point detection, evaluated against human annotations on the Turing Change Point Dataset (TCPD). Constant, linear, mean-and-variance and Bayesian segment models with exact, pruned, greedy and online search are scored by covering and F1, the benchmark's published outputs are replicated, and every number in the accompanying article is checked against the committed results.

Academic project for The Algorithms Design course. Fall 2018

This project contains multiple solutions to the classical making change problem. There are three solutions present: recursive with memoization, recursive without memoization, and a dynamic programming bottom up solution with memoization.