ICML 2007
Quantum clustering algorithms
Abstract
By the term "quantization", we refer to the process of using quantum mechanics in order to improve a classical algorithm, usually by making it go faster. In this paper, we initiate the idea of quantizing clustering algorithms by using variations on a celebrated quantum algorithm due to Grover. After having introduced this novel approach to unsupervised learning, we illustrate it with a quantized version of three standard algorithms: divisive clustering, k -medians and an algorithm for the construction of a neighbourhood graph. We obtain a significant speedup compared to the classical approach.
Authors
Keywords
No keywords are indexed for this paper.
Context
- Venue
- International Conference on Machine Learning
- Archive span
- 1993-2025
- Indexed papers
- 16471
- Paper id
- 965593124800226722