Efficient query of high-dimensional structures with points/high-dimensional structures. (Update: Mar 21 2013, in progress)
Note: This page is no longer maintained. The most updated version can be found at http://sunju.org/research/subspace-search/
- Near-optimal hashing algorithms for approximate nearest neighbor in high dimension (Simplified Journal Version in 2012)
- Efficient point-to-subspace query in L^1 with applications to robust face recognition (ECCV)
- Dimensionality reductions in L2 that preserve volumes and distance to affine spaces (DCG 2007)
- Approximate nearest subspace search (PAMI 2011)
- Hashing hyperplane queries to near points with applications to large-scale active learning (NIPS 2011)
- Subspace embeddings for the L1-norm with applications (STOC 2011)
- Dimension reduction in L1 (from TCS math – a wordpress blog by Prof. James R. Lee)
- List of open problems on embeddings of finite metric spaces (by Prof. Jiri Matousek)
- Lecture notes on metric embedding (by Prof. Jiri Matousek)
– Disclaimer– This page is meant to serve a hub for reference on this problem, and does not reflect any personal endorsement of papers listed here. So I do not hold any responsibility for quality and technical correctness of each paper. The reader is advised to use this resource with discretion.
– If you’d like your paper to be listed here – Just drop me a few lines via email (which can be found on “Welcome” page). If you don’t bother to spend a word, just deposit your paper on arXiv. I get email alert about new animals there every morning (eps. under the CS category), and will be happy to hunt one for this zoo if it seems *fit*.