Proximal Methods Avoid Active Strict Saddles of Weakly Convex Functions.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 561, doi. 10.1007/s10208-021-09516-w
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Works matching IS 16153375 AND DT 2022 AND VI 22 AND IP 2
Results: 8
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A Theoretical and Empirical Comparison of Gradient Approximations in Derivative-Free Optimization.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 507, doi. 10.1007/s10208-021-09513-z
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- Article
3
A New Technique for Preserving Conservation Laws.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 477, doi. 10.1007/s10208-021-09511-1
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- Article
4
A Counter-Example to Hausmann's Conjecture.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 469, doi. 10.1007/s10208-021-09510-2
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- Article
5
A New Upper Bound for Sampling Numbers.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 445, doi. 10.1007/s10208-021-09504-0
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- Article
6
Primal Dual Methods for Wasserstein Gradient Flows.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 389, doi. 10.1007/s10208-021-09503-1
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- Article
7
Optimization Over the Boolean Hypercube Via Sums of Nonnegative Circuit Polynomials.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 365, doi. 10.1007/s10208-021-09496-x
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- Article
8
Convergence of Adaptive Discontinuous Galerkin and C0-Interior Penalty Finite Element Methods for Hamilton–Jacobi–Bellman and Isaacs Equations.
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- Foundations of Computational Mathematics, 2022, v. 22, n. 2, p. 315, doi. 10.1007/s10208-021-09493-0
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- Article