High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.
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Updated
Nov 12, 2024 - Julia
High performance nearest neighbor data structures (KDTree and BallTree) and algorithms for Julia.
Octree/Quadtree/N-dimensional linear tree
A Python implementation of Priority R-Tree, an alternative to RTree.
Memory-resident B+ tree implementation, supporting insertion, key based search, bound based search and range search operations.
Julia wrapper around the Faiss library for similarity search with PythonCall.jl
On-Disk Implementation of R-Tree with Insertion and Bulk Load. This data structure efficiently stores and retrieve multi-dimensional data, very similar to B+ Tree where data is 1D though.
Create a symbol table data type whose keys are two-dimensional points. Use a 2d-tree to support efficient range search and nearest neighbor search.
Neighbor Search and Clustering for Vectors using Locality-sensitive hashing and Randomized Projection to Hypercube
Vectors - Nearest neighbor search and Clustering using LSH, Hypercube (and Lloyd's only at the clustering) algorithms with L2 metric.
Master's thesis titled "MAKING LARGE TRANSFERS FAST FOR IN-MEMORY DATABASES IN MODERN NETWORKS". Style files forked off from the sample thesis from @fishcorn. To compile go to "thesis" folder and run `make`.
AngularJS functionality to query the server for events either from the user's current location using HTML5 Geolocation or the user's city preference's coordinates. Remove event if the distance between it and the user's location is bigger than the specified range of miles.
A generic binary search tree implementation in C# featuring tree traversals, range search and rebalancing.
📝 Inserting numbering plan data from the site https://rossvyaz.gov.ru/ in the Oracle database and a quick search in the inserted data
Search and clustering vectors in C++
📐 This project implements various computational geometry algorithms, focusing on convex hulls, linear programming, Delaunay triangulation, and geometric search. The code is organized into multiple modules, each solving specific geometry-related problems and demonstrating core computational methods.
my solution to interview bit problem
Implemented B+ Tree for executing range queries on large SQL records
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