Well-Tempered Clavier
... • New key-profile values – New problem: Repetitions of notes affect result ...
... • New key-profile values – New problem: Repetitions of notes affect result ...
IPESA-II
... archive, the grid environment will need to be checked. Any excess of the grid boundary or the upper limit of the archive size will lead to the adjustment (or even reconstruction) of the grid environment. This not only causes extra time consumption, but also affects the uniformity of the final archiv ...
... archive, the grid environment will need to be checked. Any excess of the grid boundary or the upper limit of the archive size will lead to the adjustment (or even reconstruction) of the grid environment. This not only causes extra time consumption, but also affects the uniformity of the final archiv ...
Lecture Notes (pptx)
... Use the size of the input rather than the input itself – n Count the number of “basic steps” rather than computing exact time Ignore multiplicative constants and small inputs (order-of, big-O) Determine number of steps for either worst-case expected-case These assumptions allow us to analyze algor ...
... Use the size of the input rather than the input itself – n Count the number of “basic steps” rather than computing exact time Ignore multiplicative constants and small inputs (order-of, big-O) Determine number of steps for either worst-case expected-case These assumptions allow us to analyze algor ...
Dynamic Programming
... problem just once and then Saves its answer in a table (array), there by Avoiding the work of recomputing the answer every time the sub problem is encountered. Dynamic programming is typically applied to optimization problems. What is an optimization problem? There can be may possible solutions ...
... problem just once and then Saves its answer in a table (array), there by Avoiding the work of recomputing the answer every time the sub problem is encountered. Dynamic programming is typically applied to optimization problems. What is an optimization problem? There can be may possible solutions ...
Q 5.2 : Consider the rough guide to worst
... Insert the bounding rectangle into the R tree, the process would be as follows. Because for R-tree, it will try to minimize the area, so it the search would go to Q->Z (Q has less enlargement than P to include new rectangle). Because the child of entry Z is full, we have to split the node which cont ...
... Insert the bounding rectangle into the R tree, the process would be as follows. Because for R-tree, it will try to minimize the area, so it the search would go to Q->Z (Q has less enlargement than P to include new rectangle). Because the child of entry Z is full, we have to split the node which cont ...
Lecture Notes (6up)
... our discussion of linked lists from two weeks ago. is the worst case complexity for appending N items on a linked list? For testing to see if the list contains X? What would be the best case complexity for these operations? ¤ If we were going to talk about O() complexity for a list, which of these ...
... our discussion of linked lists from two weeks ago. is the worst case complexity for appending N items on a linked list? For testing to see if the list contains X? What would be the best case complexity for these operations? ¤ If we were going to talk about O() complexity for a list, which of these ...
Research Summary - McGill University
... predictive representation. PSR groups together states which behave similarly and it holds the promise of a more compact representation than POMDPs. We point out special cases in which strict reduction in the number of states is obtained by linear PSRs [3]. Another aspect of PSR study is learning the ...
... predictive representation. PSR groups together states which behave similarly and it holds the promise of a more compact representation than POMDPs. We point out special cases in which strict reduction in the number of states is obtained by linear PSRs [3]. Another aspect of PSR study is learning the ...
Introduce methods of analyzing a problem and developing a
... • Once the problem has been properly defined, you usually begin with a rough sketch of the steps required to solve the problem • The first attempt at designing a particular algorithm usually does not result in a finished product ...
... • Once the problem has been properly defined, you usually begin with a rough sketch of the steps required to solve the problem • The first attempt at designing a particular algorithm usually does not result in a finished product ...
CHAPTER 3
... Give a set S of n numbers,there is a number p which divides S into three subsets S1,S2and S3. case1:the size of S is greater than k.Kth smallest of S must be located in S1 ,prune away S2 and S3. case2:the condition of Case1 is not valid.But the size of S1 and S2 is greater than k.the kth smallest nu ...
... Give a set S of n numbers,there is a number p which divides S into three subsets S1,S2and S3. case1:the size of S is greater than k.Kth smallest of S must be located in S1 ,prune away S2 and S3. case2:the condition of Case1 is not valid.But the size of S1 and S2 is greater than k.the kth smallest nu ...
SPAA: Symposium on Parallelism in Algorithms and Architectures
... detectors, which key component is a series-parallel maintenance algorithm. In this paper Robert Utterback, Kunal Agrawal, Jeremy T. Fineman and I-Ting Angelina Lee introduce the asymptotically optimal WSP-Order algorithm. The second part of the paper describes C-RACER, a race detector using WSP-Orde ...
... detectors, which key component is a series-parallel maintenance algorithm. In this paper Robert Utterback, Kunal Agrawal, Jeremy T. Fineman and I-Ting Angelina Lee introduce the asymptotically optimal WSP-Order algorithm. The second part of the paper describes C-RACER, a race detector using WSP-Orde ...
Shortest and Closest Vectors
... It is not difficult to see that when we use Gram-Schmidt formula bi = b̃i + j=1 µi, j b̃j and the previous two claims, we can bound it by max1≤i≤n 4nDB4 kbi k which is still polynomial number of bits in n. This finally proves that the LLL algorithm runs in polynomial time. ...
... It is not difficult to see that when we use Gram-Schmidt formula bi = b̃i + j=1 µi, j b̃j and the previous two claims, we can bound it by max1≤i≤n 4nDB4 kbi k which is still polynomial number of bits in n. This finally proves that the LLL algorithm runs in polynomial time. ...
Logarithms in running time
... Logarithms in Running Time Binary search Euclid’s algorithm Exponentials Rules to count operations ...
... Logarithms in Running Time Binary search Euclid’s algorithm Exponentials Rules to count operations ...
ppt
... The average time taken by an algorithm when each possible instance of a given size is equally likely. Expected time The mean time that it would take to solve the same instance over and over. Prabhas Chongstitvatana ...
... The average time taken by an algorithm when each possible instance of a given size is equally likely. Expected time The mean time that it would take to solve the same instance over and over. Prabhas Chongstitvatana ...
Lecture Notes
... If we were going to talk about O() complexity for a list, which of these makes more sense: worst, average or best-case complexity? Why? ...
... If we were going to talk about O() complexity for a list, which of these makes more sense: worst, average or best-case complexity? Why? ...
slides
... Randomized Quicksort Always output correct answer Takes O(N log N) time on average Likelihood of running O(N log N) time? ...
... Randomized Quicksort Always output correct answer Takes O(N log N) time on average Likelihood of running O(N log N) time? ...
PPT
... Divide and Conquer Divide up the problem into at least two sub-problems Solve all sub-problems: Mergesort ...
... Divide and Conquer Divide up the problem into at least two sub-problems Solve all sub-problems: Mergesort ...
expositions
... problem 4.5 Lomuto Partitioning with Quickselect: Explain how it works and demonstrate Quickselect 4.5 Game of Nim: Discuss solutions to variants of Nim, Explain convincingly how the binary sum technique works 5.1 (Mergesort) 5.2 Quicksort: Compare to Quicksort in detail – when would each be used? 5 ...
... problem 4.5 Lomuto Partitioning with Quickselect: Explain how it works and demonstrate Quickselect 4.5 Game of Nim: Discuss solutions to variants of Nim, Explain convincingly how the binary sum technique works 5.1 (Mergesort) 5.2 Quicksort: Compare to Quicksort in detail – when would each be used? 5 ...