5 citations · 7 across the 6 of their papers we have counts for
4 papers · 1 filter
Hyperbolic Continuous Structural Entropy for Hierarchical Clustering
Guangjie Zeng, Hao Peng, Angsheng Li +5
Hierarchical clustering is a fundamental machine-learning technique for grouping data points into dendrograms. However, existing hierarchical clustering methods encounter two prima…
Structural Information-based Hierarchical Diffusion for Offline Reinforcement Learning
Xianghua Zeng, Hao Peng, Angsheng Li +1
Diffusion-based generative methods have shown promising potential for modeling trajectories from offline reinforcement learning (RL) datasets, and hierarchical diffusion has been i…
Structural Optimization Makes Graph Classification Simpler and Better
Junran Wu, Jianhao Li, Yicheng Pan +1
In deep neural networks, better results can often be obtained by increasing the complexity of previously developed basic models. However, it is unclear whether there is a way to bo…
An Information-theoretic Perspective of Hierarchical Clustering
Yicheng Pan, Feng Zheng, Bingchen Fan
A combinatorial cost function for hierarchical clustering was introduced by Dasgupta \cite{dasgupta2016cost}. It has been generalized by Cohen-Addad et al. \cite{cohen2019hierarchi…