@Atul: The initial heap is given. You have to maintain the heap
property as k elements are removed, which is O(k log n). This does not
satisfy the original request for an algorithm that is "O(k) in the
worst-case, independent of the size of the heap."

Dave

On Dec 13, 10:31 pm, atul anand <atul.87fri...@gmail.com> wrote:
> @gaurav : you need to first build heap and then maintain heap property ever
> time you remove element.so this would take O(n logn ).
>
>
>
> On Wed, Dec 14, 2011 at 1:38 AM, Gaurav Kumar <gkuma...@gmail.com> wrote:
> > Why can't we keep removing the minimum element each time and compare it
> > with x? This should take O(k) time since in a Min heap, the minimum element
> > can be removed in O(1) time? Am I missing something?
>
> > On Tue, Dec 13, 2011 at 8:43 AM, atul anand <atul.87fri...@gmail.com>wrote:
>
> >> O(k) in the worst-case , then i guess it would better to use
> >> median-of median algo to find element at rank k. and comparing with x.
>
> >> or
> >> we can us hashtable to solve this.
>
> >> On Tue, Dec 13, 2011 at 3:23 PM, Ankur Garg <ankurga...@gmail.com> wrote:
>
> >>> Given an array-based heap on n elements and a real number x, efficiently
> >>> determine whether the kth smallest element in the heap is greater than or
> >>> equal to x. Your algorithm should be O(k) in the worst-case, independent 
> >>> of
> >>> the size of the heap.
>
> >>> This question was also asked in Amazon
>
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