74 citations · 355 across the 31 of their papers we have counts for
14 papers · 1 filter
Sequential locality of graphs and its hypothesis testing
Tatsuro Kawamoto, Teruyoshi Kobayashi
The adjacency matrix is the most fundamental and intuitive object in graph analysis that is useful not only mathematically but also for visualizing the structures of graphs. Becaus…
Graph-based open-ended survey on concerns related to COVID-19
Tatsuro Kawamoto, Takaaki Aoki, Michiko Ueda
The COVID-19 pandemic is an unprecedented public health crisis with broad social and economic consequences. We conducted four surveys between April and August 2020 using the graph-…
Spectral clustering of annotated graphs using a factor graph representation
Tatsuro Kawamoto
Graph-structured data commonly have node annotations. A popular approach for inference and learning involving annotated graphs is to incorporate annotations into a statistical mode…
Fragility of spectral clustering for networks with an overlapping structure
Chihiro Noguchi, Tatsuro Kawamoto
Communities commonly overlap in real-world networks. This is a motivation to develop overlapping community detection methods, because methods for non-overlapping communities may no…
Democratic summary of public opinions in free-response surveys
Tatsuro Kawamoto, Takaaki Aoki
Social surveys have been widely used as a method of obtaining public opinion. Sometimes it is more ideal to collect opinions by presenting questions in free-response formats than i…
Evaluating network partitions through visualization
Chihiro Noguchi, Tatsuro Kawamoto
Network clustering requires making many decisions manually, such as the number of groups and a statistical model to be used. Even after filtering using an information criterion or…
Algorithmic infeasibility of community detection in higher-order networks
Tatsuro Kawamoto
In principle, higher-order networks that have multiple edge types are more informative than their lower-order counterparts. In practice, however, excessively rich information may b…
Algorithmic detectability threshold of the stochastic block model
Tatsuro Kawamoto
The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the s…
Detectability thresholds of general modular graphs
Tatsuro Kawamoto, Yoshiyuki Kabashima
We investigate the detectability thresholds of various modular structures in the stochastic block model. Our analysis reveals how the detectability threshold is related to the deta…
Comparative analysis on the selection of number of clusters in community detection
Tatsuro Kawamoto, Yoshiyuki Kabashima
We conduct a comparative analysis on various estimates of the number of clusters in community detection. An exhaustive comparison requires testing of all possible combinations of f…
Cross-validation estimate of the number of clusters in a network
Tatsuro Kawamoto, Yoshiyuki Kabashima
Network science investigates methodologies that summarise relational data to obtain better interpretability. Identifying modular structures is a fundamental task, and assessment of…
Detectability of the spectral method for sparse graph partitioning
Tatsuro Kawamoto, Yoshiyuki Kabashima
We show that modularity maximization with the resolution parameter offers a unifying framework of graph partitioning. In this framework, we demonstrate that the spectral method exh…
Localized eigenvectors of the non-backtracking matrix
Tatsuro Kawamoto
In the case of graph partitioning, the emergence of localized eigenvectors can cause the standard spectral method to fail. To overcome this problem, the spectral method using a non…
Limitations in the spectral method for graph partitioning: detectability threshold and localization of eigenvectors
Tatsuro Kawamoto, Yoshiyuki Kabashima
Investigating the performance of different methods is a fundamental problem in graph partitioning. In this paper, we estimate the so-called detectability threshold for the spectral…