5 citations · 14 across the 14 of their papers we have counts for
14 papers
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…
A Simple yet Effective Method for Graph Classification
Junran Wu, Shangzhe Li, Jianhao Li +2
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…
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…
The idemetric property: when most distances are (almost) the same
George Barmpalias, Neng Huang, Andrew Lewis-Pye +4
We introduce the \emph{idemetric} property, which formalises the idea that most nodes in a graph have similar distances between them, and which turns out to be quite standard among…
Structure Entropy and Resistor Graphs
Angsheng Li, Yicheng Pan
We propose the notion of {\it resistance of a graph} as an accompanying notion of the structure entropy to measure the force of the graph to resist cascading failure of strategic v…
Rectangle Transformation Problem
Shaojiang Wang, Kun He, Yicheng Pan +1
In this paper, we propose the rectangle transformation problem (RTP) and its variants. RTP asks for a transformation by a rectangle partition between two rectangles of the same are…
Community Structures Are Definable in Networks: A Structural Theory of Networks
Angsheng Li, Yicheng Pan, Jiankou Li
We found that neither randomness in the ER model nor the preferential attachment in the PA model is the mechanism of community structures of networks, that community structures are…
Provable Security of Networks
Angsheng Li, Yicheng Pan, Wei Zhang
We propose a definition of {\it security} and a definition of {\it robustness} of networks against the cascading failure models of deliberate attacks and random errors respectively…
Homophyly Networks -- A Structural Theory of Networks
Angsheng Li, Jiankou Li, Yicheng Pan
A grand challenge in network science is apparently the missing of a structural theory of networks. The authors have showed that the existence of community structures is a universal…
Community Structures Are Definable in Networks, and Universal in Real World
Angsheng Li, Jiankou Li, Yicheng Pan
Community detecting is one of the main approaches to understanding networks \cite{For2010}. However it has been a longstanding challenge to give a definition for community structur…
Dimensions, Structures and Security of Networks
Angsheng Li, Wei Zhang, Yicheng Pan
One of the main issues in modern network science is the phenomenon of cascading failures of a small number of attacks. Here we define the dimension of a network to be the maximal n…
Homophyly and Randomness Resist Cascading Failure in Networks
Angsheng Li, Wei Zhang, Yicheng Pan +1
The universal properties of power law and small world phenomenon of networks seem unavoidably obstacles for security of networking systems. Existing models never give secure networ…