Lecture-13
... Recursion is very powerful way to solve certain problems for which the solution would otherwise be very complicated. There are many problems and specific areas where you can see the repetitive behaviour (pattern) or you can find a thing, which can be modelled in such a way that it repeats itself ...
... Recursion is very powerful way to solve certain problems for which the solution would otherwise be very complicated. There are many problems and specific areas where you can see the repetitive behaviour (pattern) or you can find a thing, which can be modelled in such a way that it repeats itself ...
An Improved Ant Colony Optimisation Algorithm for the 2D HP
... Protein Folding Problem incorporates a local search phase. In this work, we modified the local search mechanism from our previous ACO algorithm by using a new type of long range move, selective local search, and improving ants that perform probabilistic iterative improvement on the best conformation ...
... Protein Folding Problem incorporates a local search phase. In this work, we modified the local search mechanism from our previous ACO algorithm by using a new type of long range move, selective local search, and improving ants that perform probabilistic iterative improvement on the best conformation ...
Reinforcement Learning for Neural Networks using Swarm Intelligence
... the cart is the track. Letting a pole fall more than 36° from vertical or running off the track constitutes failure. To prove itself to be a valid solution, an ANN must pass 10 trials, each lasting 100,000 simulation steps. ...
... the cart is the track. Letting a pole fall more than 36° from vertical or running off the track constitutes failure. To prove itself to be a valid solution, an ANN must pass 10 trials, each lasting 100,000 simulation steps. ...
Elementary Properties of the Integers
... Theorem (2-2). If a and b are integers, not both zero, then gcd(a, b) exists and is unique. Note that this result is trivial if either a or b is zero. Also note that changing the sign of a or b or swapping a for b does not change the gcd. Without loss of generality, we may thus assume that 0 < b ≤ a ...
... Theorem (2-2). If a and b are integers, not both zero, then gcd(a, b) exists and is unique. Note that this result is trivial if either a or b is zero. Also note that changing the sign of a or b or swapping a for b does not change the gcd. Without loss of generality, we may thus assume that 0 < b ≤ a ...
Data Discretization
... intervals that minimize the value of X2. • Yang and Webb studied discretization using naïve Bayesian classifiers. They report that their method generates a lower number of classification errors than the alternative discretization methods that appeared in literature ...
... intervals that minimize the value of X2. • Yang and Webb studied discretization using naïve Bayesian classifiers. They report that their method generates a lower number of classification errors than the alternative discretization methods that appeared in literature ...
2 - R
... [3] M. Tipping and A. Faul, "Fast marginal likelihood maximisation for sparse Bayesian models," in Proc. 9th Int. Workshop Artificial Intelligence and Statistics, C. M. Bishop and B. J. Frey, Eds., ...
... [3] M. Tipping and A. Faul, "Fast marginal likelihood maximisation for sparse Bayesian models," in Proc. 9th Int. Workshop Artificial Intelligence and Statistics, C. M. Bishop and B. J. Frey, Eds., ...
Slide 1
... • We can see that n!=n*(n-1)!. If we go further, n!=n*(n1)*(n-2)!. This can continue until 0 is encountered, which gives 1. • Hence this can be achieved by having a function which calls itself until 0 is encountered. This is recursive function for factorial. ...
... • We can see that n!=n*(n-1)!. If we go further, n!=n*(n1)*(n-2)!. This can continue until 0 is encountered, which gives 1. • Hence this can be achieved by having a function which calls itself until 0 is encountered. This is recursive function for factorial. ...
Enhanced form of solving real coded numerical optimization
... solutions depending on the information of their fitness values. Population based algorithm is classified into two groups: evolutionary algorithms [3] and swarm intelligence-based algorithms [4]. Evolutionary algorithm is one of the most popular genetic algorithm (GA) based on the natural evolution. ...
... solutions depending on the information of their fitness values. Population based algorithm is classified into two groups: evolutionary algorithms [3] and swarm intelligence-based algorithms [4]. Evolutionary algorithm is one of the most popular genetic algorithm (GA) based on the natural evolution. ...
CHAPTER 4: LAZY KERNEL-DENSITY
... and kernel-ridge regression [9]. All of these techniques have in common that a lossfunction is minimized to result in a classifier that is optimal according to some definition [10]. This optimization step is not, however, the defining element of kernel methods. Clustering techniques that are well-es ...
... and kernel-ridge regression [9]. All of these techniques have in common that a lossfunction is minimized to result in a classifier that is optimal according to some definition [10]. This optimization step is not, however, the defining element of kernel methods. Clustering techniques that are well-es ...