Algorithms Lecture 19: Dynamic Programming, Longest Common Subsequence and Longest Common Substring
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- Опубліковано 12 вер 2024
- California State University, Sacramento
Spring 2018
Algorithms
by Ghassan Shobaki
Text book: Introduction to Algorithms by Cormen, Leiserson, Rivest, and Stein, 3rd Edition, MIT Press, Cambridge (2009)
Thank you so much, sir, this was exactly I was looking for, other videos on youtube just taught how to fill the table whether to go diagonal or up or left but didn't explain the formula behind, but you explained to the point. I am grateful. Thanks, Love from India.
If i was in his class i would never ever miss or jump his class.
Literally never.
Students having professors like him are so lucky
Wow! What a lecture. I have been trying to grasp this algorithm for a long time and it was pretty hard. I finally got it after this brilliant explanation. Thanks so much, Professor! One thing I wanted to mention is that after some trying to get it working on my machine, I learnt that access to x and y strings should be @ index i-1 and not i since we increase the size of dp array by 1
I've been grateful for your uploadings, many thanks to the professor for demystifying the dynamic programming technique, wish you all the best!
Thank you so much Professor Ghassan. You are gifted in teaching!
I knew the solution to this already but the way he explained is so intuitive. @14:00 It was so awesome.
Thank you so much. Don't stop uploading videos. Forever grateful.
best session on common substring problem. Thanks you sir.
This is the clearest and best explanation that I've met! Thank you very much for sharing this with us.
the best explanation of longest common substring. Thank you sir
Thank you so much for uploading this..only video which explains everything about LCS
This is definitely the best explanation I've seen yet
You explain so well!
The best prof. ever
Thanks prof, wonder how equals cases is possible in the nested else at 38:00?
n0w i underst00d the c0ncet f DP , thank y0u
Biswajeet sethi ....wheon “o” key doesnt work.
Shouldn't the complexity of constructing LCS(longest common subsequence) should Min(m,n) because there is an && in while loop so which ever i or j becomes 0 first that is how much time loop will be executed.
Correct me if wrong
No, that's not true, because they don't get both decremented in each iteration of the loop. In some iterations, only one of them will get decremented and we don't know which one.
@@ghassanshobakicomputerscie9478 got it sir thank you so so so much for replying and uploading these lectures.
You are an extremely knowledgeable person please never stop uploading.
thnkx