Articles tagged with approximate nearest neighbors

New approximate nearest neighbor benchmarks

As some of you may know, one of my side interests is approximate nearest neighbor algorithms. I'm the author of Annoy, a library with 3,500+ stars on Github as of today. It offers fast approximate search for nearest neighbors with the additional benefit that you can load data super fast from disk using mmap.

New benchmarks for approximate nearest neighbors

UPDATE(2018-06-17): There are is a later blog post with newer benchmarks! One of my super nerdy interests include approximate algorithms for nearest neighbors in high-dimensional spaces. The problem is simple. You have say 1M points in some high-dimensional space.

Annoy 1.10 released, with Hamming distance and Windows support

I've been a bit bad at posting things with a regular cadence lately, partly because I'm trying to adjust to having a toddler, partly because the hunt for clicks has caused such a high bar for me that I feel like I have to post something Pulitzer-worthy.

Approximate nearest news

As you may know, one of my (very geeky) interests is Approximate nearest neigbor methods, and I'm the author of a Python package called Annoy. I've also built a benchmark suite called ann-benchmarks to compare different packages.

Nearest neighbor methods and vector models – part 1

This is a blog post rewritten from a presentation at NYC Machine Learning last week. It covers a library called Annoy that I have built that helps you do (approximate) nearest neighbor queries in high dimensional spaces.

Benchmark of Approximate Nearest Neighbor libraries

Annoy is a library written by me that supports fast approximate nearest neighbor queries. Say you have a high (1-1000) dimensional space with points in it, and you want to find the nearest neighbors to some point.

Better precision and faster index building in Annoy

Sometimes you have these awesome insights. A few days ago I got an idea for how to improve index building in Annoy. For anyone who isn't acquainted with Annoy – it's a C++ library with Python bindings that provides fast high-dimensional nearest neighbor search.

Annoy – now without Boost dependencies and with Python 3 Support

Annoy is a C++/Python package I built for fast approximate nearest neighbor search in high dimensional spaces. Spotify uses it a lot to find similar items. First, matrix factorization gives a low dimensional representation of each item (artist/album/track/user) so that every item is a k-dimensional vector, where k is typically 40-100.