NDLE 2016
... Why is computational thinking important? Key questions: Is this the most efficient way to solve the problem? ...
... Why is computational thinking important? Key questions: Is this the most efficient way to solve the problem? ...
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... 2x3 + 4y 3 on the set S = {x2 + y 2 ≤ 1}. (The maximum theorem tells us that there is a global max/min on S. If the min or max occurs in the interior of S, we can find it by looking at the gradient of f . If the min/max doesn’t occur in the interior, we can find it using Lagrange multipliers on the ...
... 2x3 + 4y 3 on the set S = {x2 + y 2 ≤ 1}. (The maximum theorem tells us that there is a global max/min on S. If the min or max occurs in the interior of S, we can find it by looking at the gradient of f . If the min/max doesn’t occur in the interior, we can find it using Lagrange multipliers on the ...
An optimal consumption problem with partial information
... We consider an optimal consumption problem where an investor tries to maximize the finite horizon expected discounted HARA utility of consumption. We treat a stochastic factor model that the mean returns of risky assets depend on underlying economic factors formulated as the solution of a linear sto ...
... We consider an optimal consumption problem where an investor tries to maximize the finite horizon expected discounted HARA utility of consumption. We treat a stochastic factor model that the mean returns of risky assets depend on underlying economic factors formulated as the solution of a linear sto ...
An eigenvalue problem in electronic structure calculations and its
... An eigenvalue problem in electronic structure calculations and its solution by spectrum slicing Dongjin Lee† , Takeo Hoshi‡ , Yuto Miyatake† , Tomohiro Sogabe† , and Shao-Liang Zhang† ...
... An eigenvalue problem in electronic structure calculations and its solution by spectrum slicing Dongjin Lee† , Takeo Hoshi‡ , Yuto Miyatake† , Tomohiro Sogabe† , and Shao-Liang Zhang† ...
1) We are thinking of opening a Broadway play, I Love You, You`re
... A desk contributes $40 to profit, and a chair contributes $25. Marketing restrictions require that the number of chairs produced be at least twice the number of desks produced. There are 20 units of wood available. a. Provide an algebraic formulation where you clearly define your decision variables ...
... A desk contributes $40 to profit, and a chair contributes $25. Marketing restrictions require that the number of chairs produced be at least twice the number of desks produced. There are 20 units of wood available. a. Provide an algebraic formulation where you clearly define your decision variables ...
18.03 Topic 1 Part I
... Problem 1. (E&P problem 1.1/36) In a city with population P the time rate of change of the number N of people infected with a contagious disease is proportional to the product of the number who have the disease and the number who do not. Write a differential equation modeling this situation. Problem ...
... Problem 1. (E&P problem 1.1/36) In a city with population P the time rate of change of the number N of people infected with a contagious disease is proportional to the product of the number who have the disease and the number who do not. Write a differential equation modeling this situation. Problem ...
Decision Making Analysis (Introduction to Operations Research)
... Decision Making Analysis (Introduction to Operations Research) Course description: Course is an introduction to operations research and related topics. The key word of the course is “optimization”. The course starts from classical differentiable optimization problems with classical constraints. The ...
... Decision Making Analysis (Introduction to Operations Research) Course description: Course is an introduction to operations research and related topics. The key word of the course is “optimization”. The course starts from classical differentiable optimization problems with classical constraints. The ...
Computational complexity theory
Computational complexity theory is a branch of the theory of computation in theoretical computer science and mathematics that focuses on classifying computational problems according to their inherent difficulty, and relating those classes to each other. A computational problem is understood to be a task that is in principle amenable to being solved by a computer, which is equivalent to stating that the problem may be solved by mechanical application of mathematical steps, such as an algorithm.A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying the amount of resources needed to solve them, such as time and storage. Other complexity measures are also used, such as the amount of communication (used in communication complexity), the number of gates in a circuit (used in circuit complexity) and the number of processors (used in parallel computing). One of the roles of computational complexity theory is to determine the practical limits on what computers can and cannot do.Closely related fields in theoretical computer science are analysis of algorithms and computability theory. A key distinction between analysis of algorithms and computational complexity theory is that the former is devoted to analyzing the amount of resources needed by a particular algorithm to solve a problem, whereas the latter asks a more general question about all possible algorithms that could be used to solve the same problem. More precisely, it tries to classify problems that can or cannot be solved with appropriately restricted resources. In turn, imposing restrictions on the available resources is what distinguishes computational complexity from computability theory: the latter theory asks what kind of problems can, in principle, be solved algorithmically.