
#1




Q1 Quadratic Programming
From that well known source, wikipedia:
Quadratic programming (QP) is a special type of mathematical optimization problem. It is the problem of optimizing (minimizing or maximizing) a quadratic function of several variables subject to linear constraints on these variables. The hardmargin SVM problem is to minimize 0.5w'w subject to (yn(w'xn + b) >= 1. So is this a quadratic programming problem? 
#2




Re: Q1 Quadratic Programming
A quadratic function of a set of variables is a linear combination of constants and products of one or two of the variables (including squares of them).
A linear constraint is an inequality which only contains a linear combination of constants and individual variables. How do these relate to your description of the hard margin SVM problem? (The variables are the components of ) 
#3




Re: Q1 Quadratic Programming
Well, the problem was to minimize wrt w and b the value w'w (which is a combination of 2 values of our variable) subject to yn(w'xn + b) >= 1 where yn and xn are constants (our training data) i.e. a linear combination of our variable w.
So, the original problem for hardmargin SVM seems like a "quadratic programming" problem  so my real question is this: why do we do the "dual" mapping to get the problem stated in terms of alpha? Is this purely to get it into a more convenient form for QP packages? I am missing something, but I don't know what :). 
#4




Re: Q1 Quadratic Programming
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#5




Re: Q1 Quadratic Programming
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Where everyone thinks alike, no one thinks very much 
#6




Re: Q1 Quadratic Programming
Thank you Professor! I understand now!

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