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Jonathan W. Siegel
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Jonathan W. Siegel11 visible / 11 total nodes / 18 links

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Co-authorshipCo-authorshipCo-authorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipWorks onAuthorshipWorks onWorks onAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalJonathan W. SiegelAJonathan W. SiegelResearcherEmbedding Dimension Lower Bounds for Universality of Deep Sets and Janossy PoolingWEmbedding Dimension Low...preprint / 2026Ali SyedAAli SyedResearcherAditya NambiarAAditya NambiarResearcherOptimal Convergence Rates for the Orthogonal Greedy AlgorithmWOptimal Convergence Rat...preprint / 2022Characterization of the Variation Spaces Corresponding to Shallow Neural NetworksWCharacterization of the...preprint / 2022Extended Regularized Dual Averaging Methods for Stochastic OptimizationWExtended Regularized Du...preprint / 2022Accelerated Optimization With Orthogonality ConstraintsWAccelerated Optimizatio...preprint / 2021Approximation Rates for Neural Networks with General Activation FunctionsWApproximation Rates for...preprint / 2021Machine LearningTMachine Learning49008 worksA Priori Analysis of Stable Neural Network Solutions to Numerical PDEsWA Priori Analysis of St...preprint / 2022
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Jonathan W. Siegel

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PaperEmbedding Dimension Lower Bounds for Universality of Deep Sets and Janossy PoolingAuthorship / preprint / 2026PersonAli SyedCo-authorship / ResearcherPersonAditya NambiarCo-authorship / ResearcherPaperOptimal Convergence Rates for the Orthogonal Greedy AlgorithmAuthorship / preprint / 2022PaperCharacterization of the Variation Spaces Corresponding to Shallow Neural NetworksAuthorship / preprint / 2022PaperExtended Regularized Dual Averaging Methods for Stochastic OptimizationAuthorship / preprint / 2022PaperAccelerated Optimization With Orthogonality ConstraintsAuthorship / preprint / 2021PaperApproximation Rates for Neural Networks with General Activation FunctionsAuthorship / preprint / 2021

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