220 citations · 2.3k across the 62 of their papers we have counts for
8 papers · 1 filter
On Binary Embedding using Circulant Matrices
Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar +2
Binary embeddings provide efficient and powerful ways to perform operations on large scale data. However binary embedding typically requires long codes in order to preserve the dis…
Binary embeddings with structured hashed projections
Anna Choromanska, Krzysztof Choromanski, Mariusz Bojarski +3
We consider the hashing mechanism for constructing binary embeddings, that involves pseudo-random projections followed by nonlinear (sign function) mappings. The pseudo-random proj…
Structured Transforms for Small-Footprint Deep Learning
Vikas Sindhwani, Tara N. Sainath, Sanjiv Kumar
We consider the task of building compact deep learning pipelines suitable for deployment on storage and power constrained mobile devices. We propose a unified framework to learn a…
Learning to Hash for Indexing Big Data - A Survey
Jun Wang, Wei Liu, Sanjiv Kumar +1
The explosive growth in big data has attracted much attention in designing efficient indexing and search methods recently. In many critical applications such as large-scale search…
Quantization based Fast Inner Product Search
Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski +1
We propose a quantization based approach for fast approximate Maximum Inner Product Search (MIPS). Each database vector is quantized in multiple subspaces via a set of codebooks, l…
Fast Online Clustering with Randomized Skeleton Sets
Krzysztof Choromanski, Sanjiv Kumar, Xiaofeng Liu
We present a new fast online clustering algorithm that reliably recovers arbitrary-shaped data clusters in high throughout data streams. Unlike the existing state-of-the-art online…