{"product_id":"advances-in-data-science-ebook","title":"Advances in Data Science","description":"\u003cp\u003eChapter 1: Randomized Iterative Methods for Tensor Regression Under the t-product.- Chapter 2: Matrix exponentials: Lie-Trotter-Suzuki fractal decomposition, Gauss Runge-Kutta polynomial formulation, and compressible features.- Chapter 3: An exploration of graph distances, graph curvature, and applications to network analysis.- Chapter 4: Time-Varying Graph Signal Recovery Using High-Order Smoothness and Adaptive Low-rankness.- Chapter 5: Graph-Directed Topic Models of Text Documents.- Chapter 6: Linear independent component analysis in Wasserstein space.- Chapter 7: Faster Hodgerank Approximation Algorithm for Statistical Ranking and User Recommendation Problems.- Chapter 8: A Comparison Study of Graph Laplacian Computation.- Chapter 9: Supervised Dimension Reduction via Local Gradient Elongation.- Chapter 10: Reducing NLP Model Embeddings for Deployment in Embedded Systems.- Chapter 11: Automated extraction of roadside slope from aerial LiDAR data in rural North Carolina.- Chapter 12: A non-parametric optimal design algorithm for population pharmacokinetics.- Chapter 13: Unrolling Deep Learning End-to-End Method for Phase Retrieval.- Chapter 14: Performance Analysis of MFCC and wav2vec on Stuttering Data.- Chapter 15: Active Learning for Reducing Gender Gaps in Undergraduate Computing and Data Science.- Chapter 16: Quantifying and Documenting Gender-Based Inequalities in the Mathematical Sciences in the United States.\u003c\/p\u003e","brand":"Cristina Garcia-Cardona","offers":[{"title":"Default Title","offer_id":53653314961735,"sku":"9783031878046","price":171.19,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0920\/5455\/2903\/files\/advances-in-data-science-ebook-cover.webp?v=1775396898","url":"https:\/\/www.cinebuch.de\/products\/advances-in-data-science-ebook","provider":"CineBuch","version":"1.0","type":"link"}