239 citations · 418 across the 38 of their papers we have counts for
38 papers
Boosting Learning for LDPC Codes to Improve the Error-Floor Performance
Hee-Youl Kwak, Dae-Young Yun, Yongjune Kim +2
Low-density parity-check (LDPC) codes have been successfully commercialized in communication systems due to their strong error correction capabilities and simple decoding process.…
Optimized Layerwise Approximation for Efficient Private Inference on Fully Homomorphic Encryption
Junghyun Lee, Eunsang Lee, Young-Sik Kim +4
Recent studies have explored the deployment of privacy-preserving deep neural networks utilizing homomorphic encryption (HE), especially for private inference (PI). Many works have…
How to Mask in Error Correction Code Transformer: Systematic and Double Masking
Seong-Joon Park, Hee-Youl Kwak, Sang-Hyo Kim +3
In communication and storage systems, error correction codes (ECCs) are pivotal in ensuring data reliability. As deep learning's applicability has broadened across diverse domains,…
Iterative Soft Decoding Algorithm for DNA Storage Using Quality Score and Redecoding
Jaeho Jeong, Hosung Park, Hee-Youl Kwak +4
Ever since deoxyribonucleic acid (DNA) was considered as a next-generation data-storage medium, lots of research efforts have been made to correct errors occurred during the synthe…
Construction of Protograph-Based Partially Doped Generalized LDPC Codes
Jaewha Kim, Jae-Won Kim, Hee-Youl Kwak +1
A generalized low-density parity-check (GLDPC) code is a class of codes, where single parity check nodes in a conventional low-density parity-check (LDPC) code are replaced by line…
Privacy-Preserving Machine Learning with Fully Homomorphic Encryption for Deep Neural Network
Joon-Woo Lee, HyungChul Kang, Yongwoo Lee +8
Fully homomorphic encryption (FHE) is one of the prospective tools for privacypreserving machine learning (PPML), and several PPML models have been proposed based on various FHE sc…