An improved alternating inertial algorithm with adaptive step-sizes for equilibrium problems with data classification experiments

Key Points

• This method shows improved performance in solving equilibrium problems with adaptive step-sizes.
• Key evidence includes a notable accuracy boost during data classification experiments, validating the algorithm's efficiency.
• Using an alternating inertial algorithm, the assessment focuses on optimizing adaptive step-sizes for data classification.
• Improvements may enable faster and more accurate solutions in complex equilibrium problem scenarios.