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Questions tagged [svm]

Support Vector Machines

1
vote
0answers
51 views

Average margin bounds for separable SVM

Suppose we're training a linear separator in the realizable PAC setting. Given $m$ labeled examples $(x_i,y_i)$ in $\mathbb R^d\times\{-1,1\}$, a (consistent) linear separator is a vector $w\in\mathbb ...
7
votes
0answers
144 views

SVM - running time for detecting if data is linearly separable?

If my understanding is correct, one way to check if a set of $m$ data points is linearly separable is to use support vector machines to find a maximum margin hyperlane for separating the data; the ...
2
votes
1answer
316 views

Are there closed-form expressions providing the VC-dimension for the multi-class case for different classifiers?

So far, I've only encountered the VC-dim for binary classifiers. I'm interested to learn how this notion can be extended to the multi-class case. Are there expressions that provide bounds on the out-...
2
votes
1answer
599 views

On the stopping criterion of coordinate descent method

I am trying to implement the coordinate descent method to solve the dual of linear SVM problem, but blocked at the stopping criterion. Consider the optimization problem \begin{equation} \min f(\...
5
votes
0answers
176 views

Complexity of the Transductive SVM training problem

The Transductive Support Vector Machine training problem is a non-convex mixed integer programming problem: Transductive Support Vector Machine training problem. $$ \begin{align} \mathop{\text{...
1
vote
0answers
361 views

Confusion related to L1 and L2 svm [closed]

I have this confusion related to L1 and L2 svm. It is given in this paper that The dual problem is given by $$ min(\alpha) = 1/2*\alpha^T\hat Q\alpha - e^T\alpha $$ subject to $$ 0 <= \alpha_i &...
0
votes
1answer
206 views

K-means with centres outside the data?

Say we want to split a cube in $\mathbb{R}^{64}$ into 10 pieces. NN, nearest-neighbor or Voronoi splits, take 10 cluster centres $c_0, \ldots, c_9$ in the cube, e.g. from K-means, then classify a new ...
4
votes
2answers
419 views

Support Vector Machines and privacy-preservation

suppose we have data matrix A m-by-n (m observations and n features) which I want to Apply SVM on it achieving privacy (Privacy-Preserving SVM) the questions are:- 1 - Is applying kernel trick ...