Approximate Nearest Subspace Search with Applications to Pattern Recognition

By Ronen Basri, Tal Hassner, Lihi Zelnik-Manor. 2007

41 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Representation & Self-Supervised Learning

How researchers see this paper

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

In Aerospace Engineering

1. Ping Li
2. Anshumali Shrivastava
3. Nati Srebro
4. Behnam Neyshabur

In Computer Vision and Pattern Recognition

1. Anshumali Shrivastava
2. Ping Li
3. Behnam Neyshabur
4. Nati Srebro
5. Sanjiv Kumar
6. Yoshua Bengio
7. Minjoon Seo
8. Pascal Vincent

In Representation & Self-Supervised Learning

1. Ping Li
2. Anshumali Shrivastava

Citations in the corpus

• Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS) (2014, methodology): “, sign random projections (SRP) [10, 3]) or 2-bit coding are often better compared to using more bits.”
• Improved Asymmetric Locality Sensitive Hashing (ALSH) for Maximum Inner Product Search (MIPS) (2014, methodology): “Prior to our work, asymmetry was applied for hashing higher order similarity [22], sketching [8], hashing different subspaces [3], a nd data dependent hashing [20] which unlike locality sensitive hashing do not come with provable runtime guarantees.”