2021 · 24 citations · 26 references
Natural SciencesComputer ScienceMathematicsAlgorithmsMachine LearningOptimizationComputational ComplexityConvex AnalysisConvex OptimizationDiscrete OptimizationNonlinear ProgrammingOptimization TheoryGlobal Search AlgorithmsGradient DescentLarge-scale Convex OptimizationLocal SearchLocal Search AlgorithmsSearch ProblemsStochastic Gradient Descent
We study search problems that can be solved by performing Gradient Descent on a bounded convex polytopal domain and show that this class is equal to the intersection of two well-known classes: PPAD and PLS. As our main underlying technical contribution, we show that computing a Karush-Kuhn-Tucker (KKT) point of a continuously differentiable function over the domain [0,1]2 is PPAD ∩ PLS-complete. This is the first natural problem to be shown complete for this class. Our results also imply that the class CLS (Continuous Local Search) - which was defined by Daskalakis and Papadimitriou as a more “natural” counterpart to PPAD ∩ PLS and contains many interesting problems - is itself equal to PPAD ∩ PLS.
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A Stochastic Approximation Method
Herbert Robbins, Sutton Monro · The Annals of Mathematical Statistics · 1951 · 9.6K citations · Full text