Explorations in the Mathematics of Data Science
portes grátis
Explorations in the Mathematics of Data Science
The Inaugural Volume of the Center for Approximation and Mathematical Data Analytics
Foucart, Simon; Wojtowytsch, Stephan
Birkhauser Verlag AG
09/2024
286
Dura
9783031664960
15 a 20 dias
Descrição não disponível.
Preface.- S-Procedure Relaxation: a Case of Exactness Involving Chebyshev Centers.- Neural networks: deep, shallow, or in between?.- Qualitative neural network approximation over R and C.- Linearly Embedding Sparse Vectors from l2 to l1 via Deterministic Dimension-Reducing Maps.- Ridge Function Machines.- Learning Collective Behaviors from Observation.- Provably Accelerating Ill-Conditioned Low-Rank Estimation via Scaled Gradient Descent, Even with Overparameterization.- CLAIRE: Scalable GPU-Accelerated Algorithms for Diffeomorphic Image Registration in 3D.- A genomic tree based sparse solver.- A qualitative difference between gradient flows of convex functions in finite- and infinite-dimensional Hilbert spaces.
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Approximation Theory;Learning Theory;Compressive Sensing;Neural Networks;Center for Approximation and Mathematical Data Analytics
Preface.- S-Procedure Relaxation: a Case of Exactness Involving Chebyshev Centers.- Neural networks: deep, shallow, or in between?.- Qualitative neural network approximation over R and C.- Linearly Embedding Sparse Vectors from l2 to l1 via Deterministic Dimension-Reducing Maps.- Ridge Function Machines.- Learning Collective Behaviors from Observation.- Provably Accelerating Ill-Conditioned Low-Rank Estimation via Scaled Gradient Descent, Even with Overparameterization.- CLAIRE: Scalable GPU-Accelerated Algorithms for Diffeomorphic Image Registration in 3D.- A genomic tree based sparse solver.- A qualitative difference between gradient flows of convex functions in finite- and infinite-dimensional Hilbert spaces.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
