2 citations · 4 across the 12 of their papers we have counts for
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A multi-layer network based on Sparse Ternary Codes for universal vector compression
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov
We present the multi-layer extension of the Sparse Ternary Codes (STC) for fast similarity search where we focus on the reconstruction of the database vectors from the ternary code…
A multi-layer image representation using Regularized Residual Quantization: application to compression and denoising
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov
A learning-based framework for representation of domain-specific images is proposed where joint compression and denoising can be done using a VQ-based multi-layer network. While it…
Regularized Residual Quantization: a multi-layer sparse dictionary learning approach
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov
The Residual Quantization (RQ) framework is revisited where the quantization distortion is being successively reduced in multi-layers. Inspired by the reverse-water-filling paradig…
Sparse Ternary Codes for similarity search have higher coding gain than dense binary codes
Sohrab Ferdowsi, Slava Voloshynovskiy, Dimche Kostadinov +1
This paper addresses the problem of Approximate Nearest Neighbor (ANN) search in pattern recognition where feature vectors in a database are encoded as compact codes in order to sp…