The dynamic programming approach uses a 2D table to store results of subproblems. We define dp[i][j] as True if the first i characters in the string s can be matched by the first j characters of the pattern p.

Base Cases:

• dp[0][0] is True because an empty pattern matches an empty string.
• dp[0][j] is True if p[j-1] is '*', otherwise False.
• dp[i][0] is False because a non-empty string cannot be matched by an empty pattern.

Fill the table using the following rules:

• If p[j-1] is '*', dp[i][j] is True if dp[i-1][j] or dp[i][j-1] is True.
• If p[j-1] is '?' or p[j-1] == s[i-1], dp[i][j] is True if dp[i-1][j-1] is True.

The greedy algorithm approach tracks the position of the last '*' in the pattern and attempts to match remaining characters greedily. We maintain two pointers, one for the string and one for the pattern. When encountering '*', we remember the positions of both pointers in order to backtrack if needed.

If characters in p and s match or if the pattern has '?', both pointers are incremented. For '*', we shift the pattern pointer and remember indices for future potential matches. If there's a mismatch after '*', we use these remembered indices to backtrack.