Time complexity is O(n log n). But the last solution I gave has O(n).

What did u not understand abt thesolution

--------------------------------------------------
Rohit Saraf
Second Year Undergraduate,
Dept. of Computer Science and Engineering
IIT Bombay
http://www.cse.iitb.ac.in/~rohitfeb14


On Sun, Apr 11, 2010 at 11:00 AM, Priyanka Chatterjee
<dona.1...@gmail.com>wrote:

>
>
> On 11 April 2010 10:46, Rohit Saraf <rohit.kumar.sa...@gmail.com> wrote:
>
>> Construct a binary tree from the data (maintain the size of subtree under
>> each node).
>> Do rotations till the left subtree does not have size k. Rotation is a
>> constant time operation.
>> Please prove the correctness of your algorithm with the time complexity
>>
>> --------------------------------------------------
>> Rohit Saraf
>> Second Year Undergraduate,
>> Dept. of Computer Science and Engineering
>> IIT Bombay
>> http://www.cse.iitb.ac.in/~rohitfeb14<http://www.cse.iitb.ac.in/%7Erohitfeb14>
>>
>>
>>
>> On Mon, Mar 29, 2010 at 11:15 AM, blackDiamond <patidarc...@gmail.com>wrote:
>>
>>> nice solution appreciate it. but your algorithm is wasting time in
>>> finding all the element...
>>> instead of that just find boundary line kth element which can help as in
>>> finding element greater that kth and element small than kth and that soluton
>>> can be done in O(N)
>>>
>>>
>>> On Sun, Mar 28, 2010 at 10:02 PM, CHERUVU JAANU REDDY <
>>> jaanu.cher...@gmail.com> wrote:
>>>
>>>>
>>>> 1) Construct max heap by taking first k elements in an array
>>>> 2) if k+1 element less than root of max heap
>>>>        a) Delete root of max heap
>>>>        b) Insert k+1 element in max heap and apply heapify method
>>>> 3) else skip the  element
>>>> 4) apply above procedure for all n elements in an array
>>>>
>>>> At last you will get k smallest elements and root is kth smallest
>>>> element in the array
>>>>
>>>> this is O(nlogk)
>>>>
>>>>
>>>>
>>>> ----------------------------------------
>>>> CHERUVU JAANU REDDY
>>>> M.Tech in CSIS
>>>>
>>>>
>>>> On Sun, Mar 28, 2010 at 8:41 PM, abhijith reddy <
>>>> abhijith200...@gmail.com> wrote:
>>>>
>>>>> Can any one tell how to do this when there are 'm' queries like "query
>>>>> i j k" find the kth largest element in between indices i->j in an array.
>>>>> When m is large even an O(n) algorithm would be slow.
>>>>> I thinking that each query could be answered in O(sqrt(n)) time
>>>>> So any suggestions ?
>>>>>
>>>>> Thanks
>>>>>
>>>>>
>>>>> On Sun, Mar 28, 2010 at 7:57 PM, blackDiamond 
>>>>> <patidarc...@gmail.com>wrote:
>>>>>
>>>>>> there are better solution of O(n) are posted in the thread.......[?].
>>>>>> using order statices ....
>>>>>>
>>>>>>
>>>>>> On Sun, Mar 28, 2010 at 6:49 PM, Mukesh Kumar thakur <
>>>>>> mukeshraj8...@gmail.com> wrote:
>>>>>>
>>>>>>> Create a temp array temp[0..k-1] of size k.
>>>>>>> 2) Traverse the array arr[k..n-1]. While traversing, keep updating
>>>>>>> the smallest element of temp[]
>>>>>>> 3) Return the smallest of temp[]
>>>>>>> Time Complexity: O((n-k)*k).
>>>>>>>
>>>>>>>
>>>>>>> try it ..............for this problem[?]
>>>>>>>
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>>>>>>
>>>>>>
>>>>>> --
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>
>
>
> --
> Thanks & Regards,
> Priyanka Chatterjee
> Third Year Undergraduate Student,
> Computer Science & Engineering,
> National Institute Of Technology,Durgapur
> India
> http://priyanka-nit.blogspot.com/
>
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