5 papers
A General Framework for Per-record Differential Privacy
Xinghe Chen, Dajun Sun, Quanqing Xu +1
Differential Privacy (DP) is a widely adopted standard for privacy-preserving data analysis, but it assumes a uniform privacy budget across all records, limiting its applicability…
A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data
Zheng Li, Weiyan Wang, Ruiyuan Li +5
The torrential influx of floating-point data from domains like IoT and HPC necessitates high-performance lossless compression to mitigate storage costs while preserving absolute da…
Rethinking LSM-tree based Key-Value Stores: A Survey
Yina Lv, Qiao Li, Quanqing Xu +4
LSM-tree is a widely adopted data structure in modern key-value store systems that optimizes write performance in write-heavy applications by using append writes to achieve sequent…
Clue-RAG: Towards Accurate and Cost-Efficient Graph-based RAG via Multi-Partite Graph and Query-Driven Iterative Retrieval
Yaodong Su, Yixiang Fang, Yingli Zhou +2
Despite the remarkable progress of Large Language Models (LLMs), their performance in question answering (QA) remains limited by the lack of domain-specific and up-to-date knowledg…
FedAPM: Federated Learning via ADMM with Partial Model Personalization
Shengkun Zhu, Feiteng Nie, Jinshan Zeng +6
In federated learning (FL), the assumption that datasets from different devices are independent and identically distributed (i.i.d.) often does not hold due to user differences, an…