precalculus inequalities

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Bzoj 2762 JLOI2011 Inequality Group Tree array

Topic: Given some inequalities such as ax+b>c, support for inserting and modifying, and asking how many inequalities are established when x=kWhen the inequality is deformed, the value range of x will be counted on the tree array when each inequality is established.Precautions:1.a can be equal to 0 at this time if B>c x∈r if BThe value of 2.x may exceed [ -1000000,1000000]3. Because there is a negative numbe

EM algorithm sniffing

method.Derivation of 2.1 logarithmic likelihood function by EM algorithmSuppose we have a sample set {x (1),..., X (M)}, which contains m independent samples. But each sample I corresponds to the category Z (i) is unknown (equivalent to clustering, contact Kmeans), also known as the implied variable, so we need to estimate the probability model P (x,z) of the parameter θ, but because it contains the implied variable z, it is difficult to use the maximum likelihood solution.That is to say our go

Statistical learning Note nine----EM algorithm

categories of the sample I z to the right of the equality of the joint probability density function and the equation to the left of the random variable x edge probability density, that is, the likelihood function, but you can see there is "and" logarithm, after the derivation form will be very complex (you can imagine the log (F1 (x) + F2 (x ) + F3 (x) + ...) Complex functions, so it is difficult to solve the unknown parameters z and θ. OK, can we make some changes to the (1) formula? We see (2

POJ 1160 Post Office//Quad inequality optimization

Http://blog.csdn.net/find_my_dream/archive/2009/12/03/4931222.aspx This blog is generally better Optimization of quadrilateral inequalities------post-office problems M[p,n] for the solution of the problem M[I,J] represents the minimum distance to establish I post office in the former J Village and State transition equations and boundary conditions are M[1,J]=W[1,J] M[i,j]=min (M[i-1,k]+w[k+1,j]) i Where W[i,j] is expressed in d[i. J] Establish a m

K Nearest Neighbor algorithm

(Bhattacharyya Distance) , in the statistics, the Bhattacharyya distance to measure the similarity of two discrete or continuous probability distributions. It is closely related to the Bhattacharyya coefficient that measures the overlap between two statistical samples or populations. Bhattacharyya distance and Bhattacharyya coefficient with a statistician who worked at the Institute of Statistics in India in the 1930s. Bhattacharya named. At the same time, the Bhattacharyya coefficient can be u

SVM explicit interpretation of 1__ linear variational problems

sides of the equation. Then the two equations above can become. But why is it possible to multiply one 1 on either side of an inequality and the other multiply by-1? Let's look at the corresponding inequality of the blue Dot, which is the expression of the dimension vector X of the sample point. For some training sample points. They are another known category labeled Volume label, here we call it y. Such words. For the Y value of the blue dot, we set it to 1. And the Y value of the black point,

Differential constraint system

The differential constraint system refers to a series of inequalities:$$ x_j-x_i \le C_{ij} (1\le I, J \le N) $$Of course i,j do not have to take 1-n, and in the case of expansion, for each (I,J), can be a number of $C _{ij}$, but we easily turn them into an inequality.Before solving the inequality group, we can analyze the nature of this inequality group.1. This inequality group can be non-solvable, such as:$ $X _1-x_2 \le-1 \ x_2-x_3 \le-1 \ x_3-x_1

Recursive counting of bzoj3244 trees

This problem bzoj above is really insane, not to output three number (ans-0.001,ans,ans+0.001),mdzz. And I'm going to copy the mark. First re-labeling in the order of the BFS (as in the case of the example), and then for Point X, make pos[x] The DFS ordinal number of x, A[i] is the first of the DFS sequence.Consider the contribution of each point, if pos[x]>pos[x+1], then if X and x+1 the same layer, obviously pos[x]On the other hand, for a[i] and a[i+1], obviously a[i+1] is not the son of A[i],

HDU 1364 (differential constraint)

and write a program this decides whether such a sequence exists or not.InputThe input consists of blocks of lines. Each block except the last corresponds to one set of problems and King's decisions about them. The first line of the block there be integers n, and m where 0 OutputThe output contains the lines corresponding to the blocks in the input. A line contains text successful conspiracy if such a sequence does not exist. Otherwise It contains text lamentable kingdom. There is no line in the

Understanding the duality problem of SVM in depth

few sections.Optimality conditions with minimal equality constraintsThe solution of support vector machine is to solve the problem of the previous section, which is the content of the optimization course.Recalling the contents of the previous section, our goal is to find the minimum value of the function under a number of constraint conditions. in the original problem of the previous section, where the constraints are inclusive inequalities, this sec

POJ 1364 King (differential constraint) (medium)

inequalities there are.Inequalities can be described like thisGiven four parameters the first number I can represent the ordinal of the sequence, and then give N, so that the front two numbers can be described as Ai+a (i+1) +...a (i+n), that is, from I to n continuous and, then give a symbol and a KiWhen the symbol for GT stands for ' > ', the symbol for LT stands for ' Then the sample can represent1 2 GT 0A1+a2+a3>02 2 lt 2A2+a3+a4Finally asked you

"PRML Reading notes-chapter1-introduction" 1.6 Information theory

(Johan Jensen). It gives the relation between the convex function value of integral and the integral value of convex function. There is a corollary to the assumption that the secant of any two points on a convex function must be above the function image of the two points, namely: version of probability theory in terms of probability theory, is aProbability measure . function swap for real valueRandom variables (in pure mathematics, there is no difference between the two). In the

HDU ACM 1006 Tick and tick

Test instructions: Three hands of a clock keep turning, they get tired of it, and when they are closer to each other, they will be happy to ask how much time they happy in a day as a percentage of the total time.Analysis: Just find a minute, they happy the time, and then the clock every 12 hours equivalent to 43,200 seconds recovery. So the total time is 43,200 seconds, only ask for in this 43200 happy time, can calculate the percentage. Enumerate 12*60 minutes, see how many seconds in a minute

Bzoj 2330 [SCOI2011] candy difference constraint SPFA version

Test Instructions: Self-Baidu, (previously done a candy upgrade version).Method: Differential constraintparsing: Recently learning the difference constraint what, this is to do the first BZ on the problem, the feeling is still relatively simple. Here's a description of 5 operations. Case Conversion Inequalities Conversion Inequalities 2 1

Ultraviolet A 515 King

UVA_515 This is a question of a differential constraint system. We set S [I] to the sum of the numbers 1st to I. In particular, S [0] = 0. The following three types of inequalities can be listed based on the question: ① When the symbol is gt: S [s + n]-S [s-1]> = k+ 1. ② When the symbol is lt: S [s + n]-S [s-1] ③ S [I]-S [I-1]> =-INF (0 Then, after creating a graph based on these inequalities, use S

List of NP-complete Problems

Constrained Scheduling· Scheduling with individual deadlines· Preemptive Scheduling· Scheduling to minimize Weighted Completion Time Shop scheduling open-Shop Scheduling· Flow-Shop Scheduling· No-Wait Flow-Shop Scheduling· Two-processor flow-shop with Bounded Buffer· Job-Shop Scheduling Miscellaneous timetable Design· Staff Scheduling· Production Planning· Deadlock Avoidance Mathematical Programming (Click link for more info and facts about Integer Programming) Integer Programming· (Click link

The small theory of algorithm--the third chapter changes the new Peach to the old character

(f(n),g(n) >= 1/2 * f(n) + 1/2 * g(n) The advantage of this inequality is that at any point N, if The Because of the symmetry, the above inequalities are g(n) > f(n) also established at the time, so, hahaha, Ω (Nether) also proved. for n > max(n1, n2), max(f(n), g(n)) > 1/2(c1 * k(n) + c3 * l(n)) Taking full advantage of the nature of Max is the key to solving this small problem ... IQ less time to fill ah ... 3.1-2Show that for any real constants A

Data stream algorithms

with data flow problems.If we want to request a function for data flow processing, it is usually a real number. Many of the basic functions have been shown to be unable to obtain exact solutions in the case of spatial sub-linearity , so we need to find estimates or approximations. So how do we judge the quality of the results of the algorithm? Suppose the output of our algorithm is. If the algorithm satisfies the following inequalities, we call the a

DW Web authoring, math, database management

DW Web page productionSet invisible elements: Edit---preferences---categories---invisible elements---settings display---complete.Item List and number: Select the text---format---list---Select a list---complete.Set up a list of items: Select the text---format---list---properties---List properties---Set category and style---complete.Set page title: Modify---Page properties---title---Set the title---complete.Add keywords: Insert---HEAD---keywords---fill in the keywords---complete.Add Note: Insert--

Shallow solution from maximum likelihood to EM algorithm

? We see (2), (2) formula is only the numerator denominator multiplied by an equal function, or there is a "sum of the logarithm" ah, or can not solve, then why do this? Let's take a look at (3) and find that (3) becomes "logarithmic and", so it's easy to take a derivative. We notice that the equal sign becomes an equal, why can it be so changed? This is the place where the Jensen inequality is greatly apparent.Jensen Inequalities:Set F is a function that defines the field as a real number, if f

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