May 18, 2017 · To facilitate fast similarity search, this paper proposes to encode the nonlinear similarity and image structure as compact binary codes.

Aug 12, 2017 · Abstract—To facilitate fast similarity search, this paper proposes to encode the nonlinear similarity and image structure as compact.

To facilitate fast similarity search, this paper proposes to encode the nonlinear similarity and image structure as compact binary codes.

A nonlinear hash function is introduced to capture the underlying relationship among data points. Thus, the dimensionality of the matrix for computation is not ...

Apr 6, 2021 · In this paper, we propose a novel method, named Nonlinear Supervised Discrete Hashing (NSDH). Specifically, NSDH consists of two components.

In this article, we focus on these tasks to implement approximate similarity search by proposing a novel hash based method named sparse hashing (SH for short).

We want the collection to be balanced, to ensure the algorithm makes progress, and sparse, to maintain a low probability of error. Lastly, we want collections.

It is shown that hashing on the basis of t-distributed stochastic neighbor embedding outperforms state-of-the-art hashing methods on large-scale benchmark ...

Jun 8, 2021 · We investigate the training of sparse layers that use different parameters for different inputs based on hashing in large Transformer models.

Apr 16, 2018 · Abstract. We establish a generic reduction from nonlinear spectral gaps of metric spaces to data- dependent Locality-Sensitive Hashing, ...