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¿Keynotes.- From Intrinsic Dimensionality to Chaos and Control: Towards a Unified Theoretical View.- The Rise of HNSW: Understanding Key Factors Driving the Adoption.- Towards a Universal Similarity Function: the Information Contrast Model and its Application as Evaluation Metric in Artificial Intelligence Tasks.- Research Track.- Finding HSP Neighbors via an Exact, Hierarchical Approach.- Approximate Similarity Search for Time Series Data Enhanced by Section Min-Hash.- Mutual nearest neighbor graph for data analysis: Application to metric space clustering.- An Alternating Optimization Scheme for Binary Sketches for Cosine Similarity Search.- Unbiased Similarity Estimators using Samples.- Retrieve-and-Rank End-to-End Summarization of Biomedical Studies.- Fine-grained Categorization of Mobile Applications through Semantic Similarity Techniques for Apps Classification.- Runs of Side-SharingTandems in Rectangular Arrays.- Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions.- Class Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification.- The Dataset-similarity-based Approach to Select Datasets for Evaluation in Similarity Retrieval.- Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback.- Accelerating k-Means Clustering with Cover Trees.- Is Quantized ANN Search Cursed? Case Study of Quantifying Search and Index Quality.- Minwise-Independent Permutations with Insertion and Deletion of Features.- SDOclust: Clustering with Sparse Data Observers.- Solving k-Closest Pairs in High-Dimensional Data using Locality- Sensitive Hashing.- Vec2Doc: Transforming Dense Vectors into Sparse Representations for Efficient Information Retrieval.- Similarity Search with Multiple-Object Queries.- Diversity Similarity Join for Big Data.- Indexing Challenge.- Overview of the SISAP 2023 Indexing Challenge.- Enhancing Approximate Nearest Neighbor Search: Binary-Indexed LSH-Tries, Trie Rebuilding, And Batch Extraction.- General and Practical Tuning Method for Off-the-Shelf Graph-Based Index: SISAP Indexing Challenge Report by Team UTokyo.- SISAP 2023 Indexing Challenge - Learned Metric Index.- Computational Enhancements of HNSW Targeted to Very Large Datasets.- CRANBERRY: Memory-Effective Search in 100M High-Dimensional CLIP Vectors.
¿Keynotes.- From Intrinsic Dimensionality to Chaos and Control: Towards a Unified Theoretical View.- The Rise of HNSW: Understanding Key Factors Driving the Adoption.- Towards a Universal Similarity Function: the Information Contrast Model and its Application as Evaluation Metric in Artificial Intelligence Tasks.- Research Track.- Finding HSP Neighbors via an Exact, Hierarchical Approach.- Approximate Similarity Search for Time Series Data Enhanced by Section Min-Hash.- Mutual nearest neighbor graph for data analysis: Application to metric space clustering.- An Alternating Optimization Scheme for Binary Sketches for Cosine Similarity Search.- Unbiased Similarity Estimators using Samples.- Retrieve-and-Rank End-to-End Summarization of Biomedical Studies.- Fine-grained Categorization of Mobile Applications through Semantic Similarity Techniques for Apps Classification.- Runs of Side-SharingTandems in Rectangular Arrays.- Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions.- Class Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification.- The Dataset-similarity-based Approach to Select Datasets for Evaluation in Similarity Retrieval.- Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback.- Accelerating k-Means Clustering with Cover Trees.- Is Quantized ANN Search Cursed? Case Study of Quantifying Search and Index Quality.- Minwise-Independent Permutations with Insertion and Deletion of Features.- SDOclust: Clustering with Sparse Data Observers.- Solving k-Closest Pairs in High-Dimensional Data using Locality- Sensitive Hashing.- Vec2Doc: Transforming Dense Vectors into Sparse Representations for Efficient Information Retrieval.- Similarity Search with Multiple-Object Queries.- Diversity Similarity Join for Big Data.- Indexing Challenge.- Overview of the SISAP 2023 Indexing Challenge.- Enhancing Approximate Nearest Neighbor Search: Binary-Indexed LSH-Tries, Trie Rebuilding, And Batch Extraction.- General and Practical Tuning Method for Off-the-Shelf Graph-Based Index: SISAP Indexing Challenge Report by Team UTokyo.- SISAP 2023 Indexing Challenge - Learned Metric Index.- Computational Enhancements of HNSW Targeted to Very Large Datasets.- CRANBERRY: Memory-Effective Search in 100M High-Dimensional CLIP Vectors.
Inhaltsverzeichnis
¿Keynotes.- From Intrinsic Dimensionality to Chaos and Control: Towards a Unified Theoretical View.- The Rise of HNSW: Understanding Key Factors Driving the Adoption.- Towards a Universal Similarity Function: the Information Contrast Model and its Application as Evaluation Metric in Artificial Intelligence Tasks.- Research Track.- Finding HSP Neighbors via an Exact, Hierarchical Approach.- Approximate Similarity Search for Time Series Data Enhanced by Section Min-Hash.- Mutual nearest neighbor graph for data analysis: Application to metric space clustering.- An Alternating Optimization Scheme for Binary Sketches for Cosine Similarity Search.- Unbiased Similarity Estimators using Samples.- Retrieve-and-Rank End-to-End Summarization of Biomedical Studies.- Fine-grained Categorization of Mobile Applications through Semantic Similarity Techniques for Apps Classification.- Runs of Side-SharingTandems in Rectangular Arrays.- Turbo Scan: Fast Sequential Nearest Neighbor Search in High Dimensions.- Class Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification.- The Dataset-similarity-based Approach to Select Datasets for Evaluation in Similarity Retrieval.- Suitability of Nearest Neighbour Indexes for Multimedia Relevance Feedback.- Accelerating k-Means Clustering with Cover Trees.- Is Quantized ANN Search Cursed? Case Study of Quantifying Search and Index Quality.- Minwise-Independent Permutations with Insertion and Deletion of Features.- SDOclust: Clustering with Sparse Data Observers.- Solving k-Closest Pairs in High-Dimensional Data using Locality- Sensitive Hashing.- Vec2Doc: Transforming Dense Vectors into Sparse Representations for Efficient Information Retrieval.- Similarity Search with Multiple-Object Queries.- Diversity Similarity Join for Big Data.- Indexing Challenge.- Overview of the SISAP 2023 Indexing Challenge.- Enhancing Approximate Nearest Neighbor Search: Binary-Indexed LSH-Tries, Trie Rebuilding, And Batch Extraction.- General and Practical Tuning Method for Off-the-Shelf Graph-Based Index: SISAP Indexing Challenge Report by Team UTokyo.- SISAP 2023 Indexing Challenge - Learned Metric Index.- Computational Enhancements of HNSW Targeted to Very Large Datasets.- CRANBERRY: Memory-Effective Search in 100M High-Dimensional CLIP Vectors.
Details
| Erscheinungsjahr: | 2023 |
|---|---|
| Genre: | Informatik, Mathematik, Medizin, Naturwissenschaften, Technik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Reihe: | Lecture Notes in Computer Science |
| Inhalt: |
xxi
310 S. 11 s/w Illustr. 92 farbige Illustr. 310 p. 103 illus. 92 illus. in color. |
| ISBN-13: | 9783031469930 |
| ISBN-10: | 3031469933 |
| Sprache: | Englisch |
| Einband: | Kartoniert / Broschiert |
| Redaktion: |
Pedreira, Oscar
Estivill-Castro, Vladimir |
| Herausgeber: | Oscar Pedreira/Vladimir Estivill-Castro |
| Auflage: | 1st edition 2023 |
| Hersteller: |
Springer
Springer International Publishing AG Lecture Notes in Computer Science |
| Verantwortliche Person für die EU: | Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com |
| Maße: | 235 x 155 x 19 mm |
| Von/Mit: | Oscar Pedreira (u. a.) |
| Erscheinungsdatum: | 06.12.2023 |
| Gewicht: | 0,505 kg |