Kazuki Nakajima (中嶋 一貴)
Assistant Professor
Graduate School of Systems Design
Tokyo Metropolitan University, Japan
News
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(2024/10) Delivered a poster presentation at AIES 2024.
Quantifying gendered citation imbalance in computer science conferences.
Kazuki Nakajima, Yuya Sasaki, Sohei Tokuno, and George Fletcher.
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(2024/10) Our two conference papers have been accepted for Complex Networks 2024.
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Inference and visualization of community structure in grant collaboration hypergraphs.
Kazuki Nakajima and Takeaki Uno.
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Estimating hyperedge size distribution via random walk on hypergraphs.
Masanao Kodakari, Kazuki Nakajima, and Masaki Aida.
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(2024/10) Implemented Python code with numba for hyper dK-series, which is 20-30 times faster than the previous version for the parameter d_v = 2 and 2.5 and achieves comparable generation time for C++ code. Randomized instances generated by the hyper dK-series in Python can be converted to the Hypergraph object of HyperNetX.
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(2024/09) Delivered a poster presentation at CCS 2024.
Non-strong community structure in collaborative research grant hypergraphs.
Kazuki Nakajima and Takeaki Uno.
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(2024/08) Our new paper is on arXiv.
Quantifying gendered citation imbalance in computer science conferences.
Kazuki Nakajima, Yuya Sasaki, Sohei Tokuno, and George Fletcher.
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(2024/07) Our paper has been accepted for AIES 2024.
Quantifying gendered citation imbalance in computer science conferences.
Kazuki Nakajima, Yuya Sasaki, Sohei Tokuno, and George Fletcher.
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(2024/07) Delivered a poster presentation at ICSSI 2024.
Quantifying citation imbalance in computer science: Gender and conference tier.
Kazuki Nakajima and Yuya Sasaki.
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(2024/06) Delivered an oral presentation on the latest work at NetSci 2024.
HyperNEO: Inference of community structure in attributed hypergraphs.
Kazuki Nakajima and Takeaki Uno. (2024). [arXiv]
