A Newton method solves the proposed L0/1-SQSSVM model with proven local quadratic convergence and reports higher accuracy plus lower runtime than prior methods on artificial and benchmark data.
Support vector machines for texture classification
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Newton Method for Soft Quadratic Surface Support Vector Machine with 0-1 Loss Function
A Newton method solves the proposed L0/1-SQSSVM model with proven local quadratic convergence and reports higher accuracy plus lower runtime than prior methods on artificial and benchmark data.