Nearest-Neighbor Methods in Learning and Vision : Theory and Practice.
Başlık:
Nearest-Neighbor Methods in Learning and Vision : Theory and Practice.
Yazar:
Shakhnarovich, Gregory.
ISBN:
9780262256957
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 online resource (280 pages)
Seri:
Neural Information Processing series
İçerik:
Contents -- Series Foreword -- Preface -- 1 Introduction -- I THEORY -- 2 Nearest-Neighbor Searching and Metric Space Dimensions -- 3 Locality-Sensitive Hashing Using Stable Distributions -- II APPLICATIONS: LEARNING -- 4 New Algorithms for Efficient High-Dimensional Nonparametric Classification -- 5 Approximate Nearest Neighbor Regression in Very High Dimensions -- 6 Learning Embeddings for Fast Approximate Nearest Neighbor Retrieval -- III APPLICATIONS: VISION -- 7 Parameter-Sensitive Hashing for Fast Pose Estimation -- 8 Contour Matching Using Approximate Earth Mover's Distance -- 9 Adaptive Mean Shift Based Clustering in High Dimensions -- 10 Object Recognition using Locality Sensitive Hashing of Shape Contexts -- Contributors -- Index.
Özet:
Advances in computational geometry and machine learning that offer new methods for search, regression, and classification with large amounts of high-dimensional data.
Notlar:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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