A Fast Similarity Matrix Calibration Method with Incomplete Query

C Ma, R Yu, Y Zhang - Proceedings of the ACM on Web Conference …, 2024 - dl.acm.org
The similarity matrix is at the core of similarity search problems. However, incomplete
observations are ubiquitous in real scenarios leading to a less accurate similarity matrix. To …

Hybrid approximate nearest neighbor indexing and search (HANNIS) for large descriptor databases

MMM Rahman, J Tešić - … Conference on Big Data (Big Data), 2022 - ieeexplore.ieee.org
In this paper, we present a novel method for efficient and effective retrieval of similar deep
descriptors. Our new hybrid method for indexing and searching for the approximate nearest …

Evaluating hybrid approximate nearest neighbor indexing and search (hannis) for high-dimensional image feature search

MMM Rahman, J Tešić - … Conference on Big Data (Big Data), 2022 - ieeexplore.ieee.org
In this paper, we evaluate the performance of a novel method for efficient and effective
retrieval of similar high-dimensional image features. The proposed solution—-hybrid …

A Matrix Calibration Method for Similarity Matrix with Incomplete Query

C Ma, R Yu, Y Zhang - The Web Conference 2024 - openreview.net
The similarity matrix is at the core of similarity search problems. However, incomplete
observations are ubiquitous in real scenarios making the similarity matrix less accurate. To …

Face Attributes Retrieval by Multi-Label Contractive Hashing

X Zhao, X Jin, X Guo - … Data Engineering and Automated Learning–IDEAL …, 2017 - Springer
Substantial increase of Internet data requires efficient storage and rapid retrieval strategy.
Hence, supervised hashing method is introduced in this issue. By mapping high …