Bioinformatics Questions
... 8. In the gap alignment problem, we discussed an algorithm in which the gap penalty function was linear affine. What does it mean for a function to be linear affine? Another possible penalty is “convex” in which the penalty is proportional to the log of the length of the gap (as opposed to linear in ...
... 8. In the gap alignment problem, we discussed an algorithm in which the gap penalty function was linear affine. What does it mean for a function to be linear affine? Another possible penalty is “convex” in which the penalty is proportional to the log of the length of the gap (as opposed to linear in ...
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 ...
COS 511: Theoretical Machine Learning Problem 1
... to hold so that t ≤ 12 − γ for some γ > 0 which is not known before boosting begins. And suppose AdaBoost is run in the usual fashion, except that the algorithm is modified to halt and output the combined classifier H immediately following the first round on which it is consistent with all of the t ...
... to hold so that t ≤ 12 − γ for some γ > 0 which is not known before boosting begins. And suppose AdaBoost is run in the usual fashion, except that the algorithm is modified to halt and output the combined classifier H immediately following the first round on which it is consistent with all of the t ...
ppt - Purdue College of Engineering
... • Each of these structures pertain to the set and the binary operation • Group: Associative, Identity element, Inverse element • Commutative Group: Add commutative ...
... • Each of these structures pertain to the set and the binary operation • Group: Associative, Identity element, Inverse element • Commutative Group: Add commutative ...
Algorithm - SSUET - Computer Science Department
... c. Best possible, Sp(n) = p i. when Tp(n) = T*(n)/p ...
... c. Best possible, Sp(n) = p i. when Tp(n) = T*(n)/p ...
Serie 3 - D-MATH
... We provide a mesh on D in the LehrFEM-structure as a .mat-file on the webpage. Write a matlab solver Call_Helmholtz_LFE.m that computes the approximate solution by pieewise linear FEM to this problem on the provided mesh. A skeleton can be downloaded from the website. Hint: The function get_BdEdges. ...
... We provide a mesh on D in the LehrFEM-structure as a .mat-file on the webpage. Write a matlab solver Call_Helmholtz_LFE.m that computes the approximate solution by pieewise linear FEM to this problem on the provided mesh. A skeleton can be downloaded from the website. Hint: The function get_BdEdges. ...
Implementing Parallel processing of DBSCAN with Map reduce
... (DBSCAN) is a data clustering algorithm proposed 1996.[1] “It is a density-based clustering algorithm: given a set of points in some space, it groups together points that are closely packed together (points with many nearby neighbors), marking as outliers points that lie alone in low-density regio ...
... (DBSCAN) is a data clustering algorithm proposed 1996.[1] “It is a density-based clustering algorithm: given a set of points in some space, it groups together points that are closely packed together (points with many nearby neighbors), marking as outliers points that lie alone in low-density regio ...
Mathematical Programming in Data Mining
... the essence of a phenomenon Binary classification problem: – discriminating between two given point sets A and B in the n-dimensional real space Rn by using as few of the ndimensions of the space as possible ...
... the essence of a phenomenon Binary classification problem: – discriminating between two given point sets A and B in the n-dimensional real space Rn by using as few of the ndimensions of the space as possible ...
Electric Heating Element
... Surface temperature: Heating element: Overheat protection: Heater body: ...
... Surface temperature: Heating element: Overheat protection: Heater body: ...
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 ...
April 4, 2014. WalkSat, part I
... end if end loop Observe that if there are s satisfying assignments τ , then each loop can succeed with probability 2sn = p So then the expected number of iterations is 1/p. Thus, the expected runtime is ≤ |Γ|2n (i.e., no better than the deterministic algorithm). WalkSAT improves on this. It is due t ...
... end if end loop Observe that if there are s satisfying assignments τ , then each loop can succeed with probability 2sn = p So then the expected number of iterations is 1/p. Thus, the expected runtime is ≤ |Γ|2n (i.e., no better than the deterministic algorithm). WalkSAT improves on this. It is due t ...
Data Mining - bhecker.com
... Expected Value of X 2nd moment is Σa (ma )2. E(X ) = (1/n )(Σall times t of n * (twice the number of times the stream element at time t appears from that time on) – 1). = Σa (1/n)(n )(1+3+5+…+2ma-1) . ...
... Expected Value of X 2nd moment is Σa (ma )2. E(X ) = (1/n )(Σall times t of n * (twice the number of times the stream element at time t appears from that time on) – 1). = Σa (1/n)(n )(1+3+5+…+2ma-1) . ...
Powerpoint Slides - Set #1 - The Stanford University InfoLab
... Expected Value of X 2nd moment is Σa (ma )2. E(X ) = (1/n )(Σall times t of n * (twice the number of times the stream element at time t appears from that time on) – 1). = Σa (1/n)(n )(1+3+5+…+2ma-1) . ...
... Expected Value of X 2nd moment is Σa (ma )2. E(X ) = (1/n )(Σall times t of n * (twice the number of times the stream element at time t appears from that time on) – 1). = Σa (1/n)(n )(1+3+5+…+2ma-1) . ...
Introduction to Algorithm
... clockwork to find the required solution, but most are less tractable and require either a very long computation or a compromise on a solution that may not be optimal.” (Richard Karp, UC berkeley) ...
... clockwork to find the required solution, but most are less tractable and require either a very long computation or a compromise on a solution that may not be optimal.” (Richard Karp, UC berkeley) ...
HW1.pdf
... In order to show that there are as many prime numbers as there are natural numbers, match each prime number with a natural number in the following manner. Create pairs of prime and natural numbers by matching the first prime number with 1(which is the first natural number) and the second prime numbe ...
... In order to show that there are as many prime numbers as there are natural numbers, match each prime number with a natural number in the following manner. Create pairs of prime and natural numbers by matching the first prime number with 1(which is the first natural number) and the second prime numbe ...
CS206 --- Electronic Commerce
... Expected Value of X 2nd moment is Σa (ma )2. E(X ) = (1/n )(Σall times t n * (twice the number of times the stream element at time t appears from that time on) – 1). = Σa (1/n)(n )(1+3+5+…+2ma-1) . ...
... Expected Value of X 2nd moment is Σa (ma )2. E(X ) = (1/n )(Σall times t n * (twice the number of times the stream element at time t appears from that time on) – 1). = Σa (1/n)(n )(1+3+5+…+2ma-1) . ...
lect1 - University of South Carolina
... The Nature of This Course This is one of the most important courses of computer science • It plays a central role in both the science and the practice of computing • It tells you how to design a program to solve important problems efficiently, effectively and professionally • The knowledge in this ...
... The Nature of This Course This is one of the most important courses of computer science • It plays a central role in both the science and the practice of computing • It tells you how to design a program to solve important problems efficiently, effectively and professionally • The knowledge in this ...
Algorithm 1.1 Sequential Search Problem Inputs Outputs
... If T(n) is O(n), then it is also O(n2), O(n3), O(n3), O(2n), .... since these are also upper bounds. Omega Definition - asymptotic lower bound For a given complexity function f(n), ( f(n) ) is the set of complexity functions g(n) for which there exists some positive real constant c and some nonnega ...
... If T(n) is O(n), then it is also O(n2), O(n3), O(n3), O(2n), .... since these are also upper bounds. Omega Definition - asymptotic lower bound For a given complexity function f(n), ( f(n) ) is the set of complexity functions g(n) for which there exists some positive real constant c and some nonnega ...
Word Pro - Mathematical Notation
... a is an element of S a is a not an element of S T contains S S is contained in T S is a subset of T A union B A intersection B acA|a"B (a, b) | a c A, b c B For each or for all If and only if There exists There exists a unique Such that Such that One to one Empty set or null implies Indicates that a ...
... a is an element of S a is a not an element of S T contains S S is contained in T S is a subset of T A union B A intersection B acA|a"B (a, b) | a c A, b c B For each or for all If and only if There exists There exists a unique Such that Such that One to one Empty set or null implies Indicates that a ...
CS-4620 Functional Programming I 2012-2013
... Returns an infinite list [ a1 , a2 , a3 , . . . ] of approximations which converge to the square root of ‘x’ (x ≥ 0). These approximations are defined by: a1 = 1.0 ai = ( ai−1 + x/ai−1 ) / 2.0, ∀ i ≥ 2 For example: take 4 ( as 2.0 ) ⇒ [ 1.0, 1.5, 1.416667, 1.414216 ] ...
... Returns an infinite list [ a1 , a2 , a3 , . . . ] of approximations which converge to the square root of ‘x’ (x ≥ 0). These approximations are defined by: a1 = 1.0 ai = ( ai−1 + x/ai−1 ) / 2.0, ∀ i ≥ 2 For example: take 4 ( as 2.0 ) ⇒ [ 1.0, 1.5, 1.416667, 1.414216 ] ...
powerpoint presentation
... Make algorithms fully understandable and interactive: Simple Dynamic Programming Table Needleman & Wunsch Smith & Waterman Local Search Four Russians ...
... Make algorithms fully understandable and interactive: Simple Dynamic Programming Table Needleman & Wunsch Smith & Waterman Local Search Four Russians ...
1 - USC
... 1. What are the essential characteristics of problems that can be solved by greedy algorithms? 2. The CS department wishes to allocate some courses to SAL 101. The list of courses are: Courses: ...
... 1. What are the essential characteristics of problems that can be solved by greedy algorithms? 2. The CS department wishes to allocate some courses to SAL 101. The list of courses are: Courses: ...
Terminology: Lecture 1 Name:_____________________
... start = time.time() sum = sumList(aList) end = time.time() print "Time to sum the list was %.3f seconds" % (end-start) def sumList(myList): """Returns the sum of all items in myList""" total = 0 for item in myList: total = total + item return total main() ...
... start = time.time() sum = sumList(aList) end = time.time() print "Time to sum the list was %.3f seconds" % (end-start) def sumList(myList): """Returns the sum of all items in myList""" total = 0 for item in myList: total = total + item return total main() ...
Weekly Handout Number 1
... • The dot in Java is equivalent to the -> C; there is no Java equivalent to the C dot operator. Generally, use -> in most cases and declare variables using the ‘*’ (indicating pointer) • There is no Boolean in C. Many programmers declare TRUE and FALSE using #define • C has no garbage collection. To ...
... • The dot in Java is equivalent to the -> C; there is no Java equivalent to the C dot operator. Generally, use -> in most cases and declare variables using the ‘*’ (indicating pointer) • There is no Boolean in C. Many programmers declare TRUE and FALSE using #define • C has no garbage collection. To ...
Instructor Rubric for Presentations
... afterwards) based on what is presented by your peer. This sheet can also be used as a study-guide for yourself, later on. ...
... afterwards) based on what is presented by your peer. This sheet can also be used as a study-guide for yourself, later on. ...