Tag: algorithms
All the articles with the tag "algorithms".
CS3016/04. Implement approximate algorithms on various variants of Travelling Salesman Problem (TSP).
Updated: 3.5 hours readUnderstand and implement approximation algorithms for classical and metric variants of the Travelling Salesman Problem (TSP), including MST-based and Christofides' heuristic.
CS3016/05. Demonstrate randomness by implementing Quicksort algorithm.
Published: 2 hours readUnderstand the concept of algorithmic randomness through randomized quicksort implementation. Analyze performance, visualize sorting, and compare with deterministic behavior.
CS3016/06. Demonstrate randomness by implementing Min-Cut algorithm.
Published: 2.5 hours readImplement and explore the randomized Min-Cut algorithm to understand the role of randomness in algorithms and graph partitioning.
CS3016/08. Implementing the Viterbi algorithm for Hidden Markov Models (HMMs)
Published: 3 hours readUnderstand and implement the Viterbi algorithm, a dynamic programming method for decoding the most likely state sequence in Hidden Markov Models.
CS3016/09. Implementing the Forward Algorithm
Published: 2.5 hours readUnderstand and implement the Forward Algorithm, a dynamic programming technique used to compute sequence probabilities in Hidden Markov Models (HMMs).
CS3016/10. Implementing algorithms from geometry problems and large data sets
Published: 3.5 hours readExplore and implement classic algorithms from computational geometry and data-intensive problems. Emphasis on real-world applications and scalable solutions.
CS3016/03. Implement approximate algorithm techniques for Vertex Cover and Steiner Tree problems.
Updated: 3 hours readLearn and implement approximation algorithms for NP-hard problems like Vertex Cover and Steiner Tree. Understand their practical importance, strategies, and performance guarantees.
CS3016/02. Program graph theory reductions among clique, vertex cover, and independent set problems.
Updated: 4 hours readTo understand and implement polynomial-time reductions among the Clique, Vertex Cover, and Independent Set problems, which are fundamental in computational complexity and NP-completeness.
CS3016/01. Implement divide-and-conquer algorithms for binary search, merge sort, and quick sort.
Published: 4 hours readTo understand and implement divide-and-conquer algorithms - Binary Search, Merge Sort, and Quick Sort, and analyze their time and space complexities.