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cs.DB2024
Why Are Learned Indexes So Effective but Sometimes Ineffective?
Qiyu Liu, Siyuan Han, Yanlin Qi +4
Learned indexes have attracted significant research interest due to their ability to offer better space-time trade-offs compared to traditional B+-tree variants. Among various lear…
cs.LG2024
PSNE: Efficient Spectral Sparsification Algorithms for Scaling Network Embedding
Longlong Lin, Yunfeng Yu, Zihao Wang +4
Network embedding has numerous practical applications and has received extensive attention in graph learning, which aims at mapping vertices into a low-dimensional and continuous d…
cs.CC2024
PSMC: Provable and Scalable Algorithms for Motif Conductance Based Graph Clustering
Longlong Lin, Tao Jia, Zeli Wang +2
Higher-order graph clustering aims to partition the graph using frequently occurring subgraphs. Motif conductance is one of the most promising higher-order graph clustering models…