On Mon, Apr 12, 2010 at 12:58 PM, Rohit Saraf
<rohit.kumar.sa...@gmail.com>wrote:

> are yaar... i meant BST... i thought that was obvious !
> sry if i confused you....
>

@rohit It's ok.Actually in this group people come up with very different and
non-common solutions so its risky to take things 'obviously'.
Rotation algo has a complexity of O(nlogn)[for constructing a BST] +O(n)
[for rotating n times]=O(nlogn) .

Till now best algo we have is using heaps which give rise to complexity =
O(n+klogn)

Please pass on algos having better runtime complexity.

>
>
> --------------------------------------------------
> Rohit Saraf
> Second Year Undergraduate,
> Dept. of Computer Science and Engineering
> IIT Bombay
> http://www.cse.iitb.ac.in/~rohitfeb14
>
>
> On Mon, Apr 12, 2010 at 12:38 PM, Nikhil Agarwal <
> nikhil.bhoja...@gmail.com> wrote:
>
>> Hey rohit.You were referring to Binary tree.Search keyword was
>> missing.Because rotation makes no sense in binary tree.Please note binary
>> tree and BST are different.
>>
>> On Mon, Apr 12, 2010 at 12:33 PM, Rohit Saraf <
>> rohit.kumar.sa...@gmail.com> wrote:
>>
>>> Read the slides i uploaded. They explain what rotation does in a BST.
>>>
>>> Also you might like to refer to Red Black Trees in CLRS.... that chapter
>>> explains rotations.
>>>
>>> --------------------------------------------------
>>> Rohit Saraf
>>> Second Year Undergraduate,
>>> Dept. of Computer Science and Engineering
>>> IIT Bombay
>>> http://www.cse.iitb.ac.in/~rohitfeb14
>>>
>>>
>>> On Mon, Apr 12, 2010 at 8:18 AM, Rohit Saraf <
>>> rohit.kumar.sa...@gmail.com> wrote:
>>>
>>>> but still the binary tree solution is of more practical use.i will
>>>> explain the solution once i reach my comp
>>>>
>>>>
>>>> On 4/11/10, Nikhil Agarwal <nikhil.bhoja...@gmail.com> wrote:
>>>> >
>>>> >
>>>> > On Sun, Apr 11, 2010 at 9:56 PM, Rohit Saraf <
>>>> rohit.kumar.sa...@gmail.com>
>>>> > wrote:
>>>> >>
>>>> >> Time complexity is O(n log n). But the last solution I gave has O(n).
>>>> >>
>>>> >> What did u not understand abt thesolution
>>>> >
>>>> >
>>>> > @Rohit Please explain how that Binary tree solution works.
>>>> >>
>>>> >>
>>>> >> --------------------------------------------------
>>>> >> 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
>>>> >>>>
>>>> >>>>
>>>> >>>>
>>>> >>>> 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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>>>> >>> Priyanka Chatterjee
>>>> >>> Third Year Undergraduate Student,
>>>> >>> Computer Science & Engineering,
>>>> >>> National Institute Of Technology,Durgapur
>>>> >>> India
>>>> >>> http://priyanka-nit.blogspot.com/
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>>>> >
>>>> >
>>>> >
>>>> >
>>>> > --
>>>> > Thanks & Regards
>>>> > Nikhil Agarwal
>>>> > Junior Undergraduate
>>>> > Computer Science & Engineering,
>>>> > National Institute Of Technology, Durgapur,India
>>>> > http://tech-nikk.blogspot.com
>>>> >
>>>> >
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>>>>
>>>> --
>>>>
>>>> --------------------------------------------------
>>>> Rohit Saraf
>>>> Second Year Undergraduate,
>>>> Dept. of Computer Science and Engineering
>>>> IIT Bombay
>>>> http://www.cse.iitb.ac.in/~rohitfeb14
>>>>
>>>
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>>
>>
>>
>> --
>> Thanks & Regards
>> Nikhil Agarwal
>> Junior Undergraduate
>> Computer Science & Engineering,
>> National Institute Of Technology, Durgapur,India
>> http://tech-nikk.blogspot.com
>>
>>
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-- 
Thanks & Regards
Nikhil Agarwal
Junior Undergraduate
Computer Science & Engineering,
National Institute Of Technology, Durgapur,India
http://tech-nikk.blogspot.com

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