Longest increasing subsequence

In summary, a longest increasing subsequence is a sequence of numbers in a given array that is in increasing order and has the maximum length compared to all other increasing subsequences in that array. It is important because it has many real-world applications and has a wide range of applications in computer science and mathematics. The time complexity of finding the longest increasing subsequence depends on the algorithm used, with the most efficient algorithm having a time complexity of O(n log n). The longest increasing subsequence can only have unique numbers and can be solved using various algorithms, such as dynamic programming, binary search, and patience sorting. The most efficient algorithm is the Patience Sorting algorithm, with a time complexity of O(n log n).
  • #1
Naumberg
1
0
Problem:

"Let [itex]x_1, ..., x_n[/itex] be i.i.d random variables uniformly on [0,1]. Let [itex]X[/itex] be the length of the longest increasing subsequence of [itex]x_1, ..., x_n[/itex]. Show that [itex]E[X] \ge (1-o(1))(1-e^{-1}) \sqrt{n}[/itex]."


Hi forum!

Using the Erdos' lemma I can only deduce that [itex]E[X] \ge \frac{1}{2} \sqrt{n}[/itex], which is a weaker bound unfortunately.

I would appreciate any further ideas!

Thanks for your help,
Michael
 
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  • #2
What does the notation "[itex] o(1) [/itex]" mean in this context?
 

What is a longest increasing subsequence?

A longest increasing subsequence is a sequence of numbers in a given array that is in increasing order and has the maximum length compared to all other increasing subsequences in that array.

Why is the longest increasing subsequence important?

The longest increasing subsequence problem is important because it has many real-world applications, such as in data compression, optimization problems, and DNA sequencing. It also has a wide range of applications in computer science and mathematics.

What is the time complexity of finding the longest increasing subsequence?

The time complexity of finding the longest increasing subsequence depends on the algorithm used. The most efficient algorithm has a time complexity of O(n log n), where n is the length of the given array.

Can the longest increasing subsequence have repeated numbers?

No, the longest increasing subsequence can only have unique numbers. However, the numbers in the subsequence do not have to be consecutive, they just need to be in increasing order.

How can the longest increasing subsequence be solved?

There are various algorithms that can be used to solve the longest increasing subsequence problem, such as dynamic programming, binary search, and patience sorting. The most efficient algorithm is the Patience Sorting algorithm, which has a time complexity of O(n log n).

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