Hash Function
Hash functions are algorithms that map data of arbitrary size to a fixed-size output, often used for data indexing, similarity search, and cryptography. Current research focuses on improving efficiency and accuracy in various applications, exploring techniques like locality-sensitive hashing (LSH), neural network-based hashing, and adaptive hashing methods tailored to specific data types (e.g., images, videos, gene sequences). These advancements are impacting diverse fields, from accelerating neural rendering and multimedia retrieval to enhancing privacy-preserving data analysis and improving the security of cryptographic systems.
Papers
Adaptive Confidence Multi-View Hashing for Multimedia Retrieval
Jian Zhu, Yu Cui, Zhangmin Huang, Xingyu Li, Lei Liu, Lingfang Zeng, Li-Rong Dai
Communication Cost Reduction for Subgraph Counting under Local Differential Privacy via Hash Functions
Quentin Hillebrand, Vorapong Suppakitpaisarn, Tetsuo Shibuya