A curve search that starts at the heavy-ball point and backtracks along a quadratic path toward the gradient yields a globally convergent momentum method with optimal O(1/ε²) worst-case complexity.
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Efficient globalization of heavy-ball type methods for unconstrained optimization based on curve searches
A curve search that starts at the heavy-ball point and backtracks along a quadratic path toward the gradient yields a globally convergent momentum method with optimal O(1/ε²) worst-case complexity.