{"product_id":"similarity-search-and-applications-9783031758225","title":"Similarity Search and Applications","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e.- Research Track.\u003cbr\u003e.- An Efficient Framework for Approximate Nearest Neighbor Search on High-dimensional Multi-metric Data.\u003cbr\u003e.- REHAB24-6: Physical Therapy Dataset for Analyzing Pose Estimation Methods.\u003cbr\u003e.- ETDD70: Eye-Tracking Dataset for Classification of Dyslexia using AI-based Methods.\u003cbr\u003e.- Demonstrating the Efficacy of Polyadic Queries.\u003cbr\u003e.- Scalable Polyadic Queries.\u003cbr\u003e.- A Dynamic Evaluation Metric for Feature Selection.\u003cbr\u003e.- Personalized Similarity Models for Evaluating Rehabilitation Exercises from Monocular Videos.\u003cbr\u003e.- Impact of the Neighborhood Parameter on Outlier Detection Algorithms.\u003cbr\u003e.- Optimizing CLIP Models for Image Retrieval with Maintained Joint-Embedding Alignment.\u003cbr\u003e.- Bayesian Estimation Approaches for Local Intrinsic Dimensionality.\u003cbr\u003e.- Towards Personalized Similarity Search for Vector Databases.\u003cbr\u003e.- Information Dissimilarity Measures in Decentralized Knowledge Distillation: A Comparative Analysis.\u003cbr\u003e.- An Empirical Evaluation of Search Strategies for Locality-Sensitive Hashing: Lookup, Voting, and Natural Classifier Search.\u003cbr\u003e.- On the Design of Scalable Outlier Detection Methods using Approximate Nearest Neighbor Graphs.\u003cbr\u003e.- A Topological Evaluation Model for Manifold Learning and Embedding Techniques.\u003cbr\u003e.- Local Intrinsic Dimensionality and the Convergence Order of Fixed-Point Iteration.\u003cbr\u003e.- Identifying Propagating Signals with Spatio-Temporal Clustering in Multivariate Time Series.\u003cbr\u003e.- Robust Statistical Scaling of Outlier Scores: Improving the Quality of Outlier Probabilities for Outliers.\u003cbr\u003e.- Advancing the PAM Algorithm to Semi-Supervised k-Medoids Clustering.\u003cbr\u003e.- Hierarchical Clustering without Pairwise Distances by Incremental Similarity Search.\u003cbr\u003e.- Indexing Challenge.\u003cbr\u003e.- Overview of the SISAP 2024 Indexing Challenge.\u003cbr\u003e.- Scaling Learned Metric Index to 100M Datasets.\u003cbr\u003e.- Grouping Sketches to Index High-Dimensional Data in a Resource Limited Setting.\u003cbr\u003e.- Adapting the Exploration Graph for high throughput in low recall regimes.\u003cbr\u003e.- Top-Down Construction of Locally Monotonic Graphs for Similarity Search.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":51043591586135,"sku":"9783031758225","price":47.49,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031758225.jpg?v=1750958793","url":"https:\/\/bookcurl.com\/products\/similarity-search-and-applications-9783031758225","provider":"Book Curl","version":"1.0","type":"link"}