TY - BOOK AU - Foucart,Simon AU - Wojtowytsch,Stephan ED - SpringerLink (Online service) TI - Explorations in the Mathematics of Data Science: The Inaugural Volume of the Center for Approximation and Mathematical Data Analytics T2 - Applied and Numerical Harmonic Analysis, SN - 9783031664977 AV - QA221-224 PY - 2024/// CY - Cham PB - Springer Nature Switzerland, Imprint: Birkhäuser KW - Approximation theory KW - Computer science KW - Mathematics KW - Information visualization KW - Quantitative research KW - Data structures (Computer science) KW - Information theory KW - Approximations and Expansions KW - Mathematical Applications in Computer Science KW - Data and Information Visualization KW - Data Analysis and Big Data KW - Data Structures and Information Theory N1 - 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 N2 - This edited volume reports on the recent activities of the new Center for Approximation and Mathematical Data Analytics (CAMDA) at Texas A&M University. Chapters are based on talks from CAMDA’s inaugural conference – held in May 2023 – and its seminar series, as well as work performed by members of the Center. They showcase the interdisciplinary nature of data science, emphasizing its mathematical and theoretical foundations, especially those rooted in approximation theory UR - https://doi.org/10.1007/978-3-031-66497-7 ER -