1 citations · 2 across the 4 of their papers we have counts for
4 papers
Differentiable Rule Induction from Raw Sequence Inputs
Kun Gao, Katsumi Inoue, Yongzhi Cao +2
Rule learning-based models are widely used in highly interpretable scenarios due to their transparent structures. Inductive logic programming (ILP), a form of machine learning, ind…
Reinforcement Logic Rule Learning for Temporal Point Processes
Chao Yang, Lu Wang, Kun Gao +1
We propose a framework that can incrementally expand the explanatory temporal logic rule set to explain the occurrence of temporal events. Leveraging the temporal point process mod…
Learning First-Order Rules with Differentiable Logic Program Semantics
Kun Gao, Katsumi Inoue, Yongzhi Cao +1
Learning first-order logic programs (LPs) from relational facts which yields intuitive insights into the data is a challenging topic in neuro-symbolic research. We introduce a nove…
Reasoning about Block-based Cloud Storage Systems
Zhao Jin, Hanpin Wang, Lei Zhang +3
Owing to the massive growth in the storage demands of big data, Cloud Storage Systems (CSSs) have been put forward to improve the storage capacity. Compared with traditional storag…