Peer to Peer Multidimensional Overlays: Approximating Complex Structures

By Olivier Beaumont, Anne-Marie Kermarrec, Etienne Riviere. 2007

40 citations recorded by the source corpus.

Subfields: ML Systems & Hardware

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In ML Systems & Hardware

1. Vladimir V. Krylov
2. Andrey Logvinov
3. Alexander Ponomarenko
4. Yury Malkov

Citations in the corpus

• Scalable Distributed Algorithm for Approximate Nearest Neighbor Search Problem in High Dimensional General Metric Spaces (2012, methodology): “In their next work [31] they have weakened the requirements on the exactness of the search in order to avoid the curse of dimensionality for the d-dimension Euclidian space.”
• Approximate nearest neighbor algorithm based on navigable small world graphs (2014, methodology): “In [13] is was shown that for Euclidean space the accuracy of a single search can be significantly increased while keeping the number of friends per node fixed.”
• Approximate Nearest Neighbor Search Small World Approach (2011, background): “The first structure for solving ANN in E with topology of small world networks is Raynet [24].”
• Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph (2017, methodology): “The algorithm in [2] approximates the small-world network by adding random long-range short-cuts among nodes and short links among closest neighbors.”
• A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search (2021, background): “To address the high degree of DG in high dimension, some slight improvements have been proposed [15, 16, 56].”