Time-dependent prediction model using modified DeepSurv algorithm for dynamic risk assessment of post-operative bone metastases in breast cancer. Hewei Ge, Jiani Wang, Xiaojia Wang, Jin Yang, ...

A comprehensive comparison of 4 algorithms for solving the 0/1 Knapsack Problem: Greedy, Dynamic Programming, Branch & Bound, and Genetic Algorithm. Includes performance analysis, visualization, and ...

Dynamic programming is one of the most challenging algorithm design techniques for computer programmers. Students frequently struggle with dynamic programming algorithms in Data Structures and ...

The team designed a fully dynamic APSP algorithm in the MPC model with low round complexity that is faster than all the existing static parallel APSP algorithms.

Visualization techniques can facilitate the extraction of meaningful patterns and trends by representing complex biological structures, dynamic processes, and large data sets in a visually intuitive ...

It covers basic algorithm design techniques such as divide and conquer, dynamic programming, and greedy algorithms. It concludes with a brief introduction to intractability (NP-completeness) .