Asymptotic Properties of Neural Network Sieve Estimators. [PDF]
J Nonparametr Stat, 2023 Shen X, Jiang C, Sakhanenko L, Lu Q.
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PRIMAL-DUAL THEORY FOR THE SUBGRADIENT METHOD IN WEAKLY-CONVEX OPTIMIZATION
Davis at al. prove the convergence rate of the subgradient method on weakly-convex functions to be O(k^−1/4). Still, the reliable stopping criterion remained unknown. This thesis establishes several computable stopping criteria from a new equivalent dual
Yan, Shengyi
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Wireless sensor network design with reliable and long network lifetime. [PDF]
Sci RepÇelik E, Keskin ME.
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Gradient Descent Provably Solves Nonlinear Tomographic Reconstruction. [PDF]
IEEE Trans Inf TheoryFridovich-Keil S +4 more
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Enhancing dance education through convolutional neural networks and blended learning. [PDF]
PeerJ Comput SciZhang Z, Wang W.
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An improved Lagrangian relaxation algorithm based SDN framework for industrial internet hybrid service flow scheduling. [PDF]
Sci Rep, 2022 Song Y, Luo W, Xu P, Wei J, Qi X.
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Hierarchical sparse spatiotemporal graph neural network for brain graph classification. [PDF]
iScienceCui J, Li Y, Qu X, Zhang Y.
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An interior point subgradient method for linearly constrained nondifferentiable convex programming
We propose in this paper an algorithm for solving linearly constrained nondifferentiable convex programming problems. This algorithm combines the ideas of the affine scaling method with the subgradient method.It is a generalization of the dual and ...
Zhang, S., Sturm, J.F., Frenk, J.B.G.
core
Universal feature selection for simultaneous interpretability of multitask datasets. [PDF]
J CheminformRaymond M +3 more
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Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness. [PDF]
J Comput Graph StatMao X, Wang H, Wang Z, Yang S.
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