Data Science and Optimization

Preface.- A General Algorithm for Assortment Optimization Under Random Utility Choice Models.- Design of Poisoning Attacks on Linear Regression Using Bilevel Optimization.- 1-norm Minimization and Minimum-Rank Structured Sparsity for Symmetric and Ah-Symmetric Generalized Inverses: Rank One and Two.- Local and Global Uniform Convexity Conditions.- A Symmetric Loss Perspective of Reliable Machine Learning.- Decoding Noisy Messages: A Method that Just Shouldn't Work.- On Reduction of the Switching Graph Problem to the Independent Set Problem.- Outer Approximations of Core Points for Integer Programming.- Sizing the White Whale.- Too Many Fairness Metrics: Is There a Solution? Equity Across Demographic Groups for the Facility Location Problem.- Adaptive First- and Second-Order Algorithms
for Large-Scale Machine Learning.- Second-Order Conditional Gradient Sliding.- Combinatorial Pure Exploration with Full-Bandit Feedback and Beyond: Solving Combinatorial Optimization Under Uncertainty with Limited Observation.

• Erscheinungsdatum: 17.02.2026
• Autor/Autorin: Sanjeena Dang,Antoine Deza,Swati Gupta,Paul D. McNicholas,Masashi Sugiyama
• Reihe: Mathematics and Statistics (R0)
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 11.5 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 342 Seiten
• ISBN: 9783032038449
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.