# Tagged Questions

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### How to find a separating hyperplane?

I know about support vector machine, and it's quadratic programming approach which delivers the best separating hyperplane. My question is: is there a relatively simple algorithm to find a ...
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### Careers in applied math with an MS other than in finance and data/machine learning?

Since I like math, I would like a career that uses alot of applied math. I'm about to complete my Master's and could do my thesis in numerical solutions of PDEs I'm already aware of careers such as ...
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I have fundamental confusion about gradient descent (with line search) and the reason it works. I try to explain my view here, and please tell me where it goes wrong. Let $f: \mathbb{R}^n \to ... 0answers 64 views ### Numerically approximate the maximum of an element of a vector after a series of matrix multiplications. Where S is a sigmoidal function, A_i is a matrix, and x is an input vector, and ... 1answer 231 views ### What is the difference between Curve Fitting and Regression(Machine Learning)? I know that Machine Learning regression algorithms try to find the function of the data. That is, if we have 1000 data points (x,y), to find a general continuous function that follows the trends of ... 1answer 189 views ### Stochastic gradient descent for convex optimization What happens if a convex objective is optimized by stochastic gradient descent? Is a global solution achieved? 0answers 48 views ### Please help me about conjugate gradient method As I know, the error function of neural network is the sum of difference between actual output and the target value. But in conjugate gradient method, they use quadratic function:$E(w) = \frac{1}{2} ...
I'm looking to paper "A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications". Author suggest to use kernel function for two distributions $p$ and $q$: \$k(p,q)= ...