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Lagrangian Support Vector Machines
An implicit Lagrangian for the dual of a simple reformulation of the standard quadratic program of a linear support vector machine is proposed. This leads to the minimization of an unconstrained di erentiable convex ...
Robust Linear and Support Vector Regression
The robust Huber M-estimator, a differentiable cost function that is quadratic for small errors and linear otherwise, is modeled exactly, in the original primal space of the problem, by an easily solvable simple convex ...
Large Scale Kernel Regression via Linear Programming
The problem of tolerant data tting by a nonlinear surface, in- duced by a kernel-based support vector machine , is formulated as a linear program with fewer number of variables than that of other linear programming ...