Derives an SMO algorithm for MAPE-based epsilon-SVR with sample-dependent box constraints that only modifies feasibility sets and clipping bounds.
Efficient SVM regression training with SMO,
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Sequential Minimal Optimization for $\varepsilon$-SVR with MAPE Loss and Sample-Dependent Box Constraints
Derives an SMO algorithm for MAPE-based epsilon-SVR with sample-dependent box constraints that only modifies feasibility sets and clipping bounds.