1 citations · 1 across the 4 of their papers we have counts for
4 papers
The Stochastic Gradient Descent for the Primal L1-SVM Optimization Revisited
Constantinos Panagiotakopoulos, Petroula Tsampouka
We reconsider the stochastic (sub)gradient approach to the unconstrained primal L1-SVM optimization. We observe that if the learning rate is inversely proportional to the number of…
The Role of Weight Shrinking in Large Margin Perceptron Learning
Constantinos Panagiotakopoulos, Petroula Tsampouka
We introduce into the classical perceptron algorithm with margin a mechanism that shrinks the current weight vector as a first step of the update. If the shrinking factor is consta…
The Perceptron with Dynamic Margin
Constantinos Panagiotakopoulos, Petroula Tsampouka
The classical perceptron rule provides a varying upper bound on the maximum margin, namely the length of the current weight vector divided by the total number of updates up to that…
The Margitron: A Generalised Perceptron with Margin
Constantinos Panagiotakopoulos, Petroula Tsampouka
We identify the classical Perceptron algorithm with margin as a member of a broader family of large margin classifiers which we collectively call the Margitron. The Margitron, (des…