#Dynamic Programming

Refer to the problem from GeeksforGeeks about the longest increasing subarray with one change allowed.

Refer to the problem on LeetCode regarding the longest continuous increasing subsequence.

Implement an algorithm to find the longest increasing subsequence in a given array of integers. You can use dynamic programming with a time complexity of O(n²) or optimize your solution with binary search to achieve a time complexity of O(n log n).

Given a matrix, find the maximum sum path from top-left to bottom-right. You can only move right or down at any point in time. For example, given the matrix [[1, 2, 3], [4, 5, 6]], the maximum sum path is 1 → 2 → 5 → 6 = 14.

Solve a dynamic programming problem that is categorized as medium to hard. Ensure you understand the problem constraints and provide a robust solution.