Sign Stable Random Projections for Large-Scale Learning

2015/04/27 by Ping Li, Li, Ping
Computer Science · Engineering · Mathematics · #Artificial intelligence #Cartography #Computation (stat.CO) #Computer science #FOS: Computer and information sciences #Geography #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Mathematical analysis #Mathematics #Physics #Scale (ratio) #Sign (mathematics) #Sparse and Compressive Sensing Techniques #Statistical physics #Topological and Geometric Data Analysis #cs.LG #stat.CO #stat.ML

paper · pdf · doi:10.48550/arxiv.1504.07235

arxiv created 2015/04/27 · openalex publication_date 2015/04/27 · arxiv updated 2015/04/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We study the use of "sign α-stable random projections" (where 0

Citations

• One Scan 1-Bit Compressed Sensing
• Coding for Random Projections
• Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
• A Method for Simulating Stable Random Variables

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