Recent Approaches and Trends in Approximate Nearest Neighbor Search, with Remarks on Benchmarking.
Nearest neighbor search is a computational primitive whose efficiency is paramount to many
applications. As such, the literature recently blossomed with many works focusing on …
applications. As such, the literature recently blossomed with many works focusing on …
TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks
Advances in machine learning research drive progress in real-world applications. To ensure
this progress, it is important to understand the potential pitfalls on the way from a novel …
this progress, it is important to understand the potential pitfalls on the way from a novel …
Locally-Adaptive Quantization for Streaming Vector Search
Retrieving the most similar vector embeddings to a given query among a massive collection
of vectors has long been a key component of countless real-world applications. The recently …
of vectors has long been a key component of countless real-world applications. The recently …
Lossless Compression of Vector IDs for Approximate Nearest Neighbor Search
Approximate nearest neighbor search for vectors relies on indexes that are most often
accessed from RAM. Therefore, storage is the factor limiting the size of the database that can …
accessed from RAM. Therefore, storage is the factor limiting the size of the database that can …
Incremental IVF Index Maintenance for Streaming Vector Search
The prevalence of vector similarity search in modern machine learning applications and the
continuously changing nature of data processed by these applications necessitate efficient …
continuously changing nature of data processed by these applications necessitate efficient …
Dynamic Exploration Graph: A Novel Approach for Efficient Nearest Neighbor Search in Evolving Multimedia Datasets
Abstract Approximate Nearest Neighbor Search (ANNS) represents a fundamental problem
in various applications (image-search, recommendation systems). While graph-based …
in various applications (image-search, recommendation systems). While graph-based …
On the Scalability and Efficiency of Graph Processing Systems
X Yin - 2024 - search.proquest.com
UNIVERSITY OF CALIFORNIA RIVERSIDE On the Scalability and Efficiency of Graph
Processing Systems A Dissertation submitted in par Page 1 UNIVERSITY OF CALIFORNIA …
Processing Systems A Dissertation submitted in par Page 1 UNIVERSITY OF CALIFORNIA …