21 citations · 44 across the 8 of their papers we have counts for
8 papers
An Accurate Graph Generative Model with Tunable Features
Takahiro Yokoyama, Yoshiki Sato, Sho Tsugawa +1
A graph is a very common and powerful data structure used for modeling communication and social networks. Models that generate graphs with arbitrary features are important basic te…
Flow-based Network Intrusion Detection Based on BERT Masked Language Model
Loc Gia Nguyen, Kohei Watabe
A Network Intrusion Detection System (NIDS) is an important tool that identifies potential threats to a network. Recently, different flow-based NIDS designs utilizing Machine Learn…
Identifying Influential Brokers on Social Media from Social Network Structure
Sho Tsugawa, Kohei Watabe
Identifying influencers in a given social network has become an important research problem for various applications, including accelerating the spread of information in viral marke…
GraphTune: A Learning-based Graph Generative Model with Tunable Structural Features
Kohei Watabe, Shohei Nakazawa, Yoshiki Sato +2
Generative models for graphs have been actively studied for decades, and they have a wide range of applications. Recently, learning-based graph generation that reproduces real-worl…
A Tunable Model for Graph Generation Using LSTM and Conditional VAE
Shohei Nakazawa, Yoshiki Sato, Kenji Nakagawa +2
With the development of graph applications, generative models for graphs have been more crucial. Classically, stochastic models that generate graphs with a pre-defined probability…
Analysis of the Convergence Speed of the Arimoto-Blahut Algorithm by the Second Order Recurrence Formula
Kenji Nakagawa, Yoshinori Takei, Shin-ichiro Hara +1
In this paper, we investigate the convergence speed of the Arimoto-Blahut algorithm. For many channel matrices the convergence is exponential, but for some channel matrices it is s…
Analysis for the Slow Convergence in Arimoto Algorithm
Kenji Nakagawa, Yoshinori Takei, Kohei Watabe
In this paper, we investigate the convergence speed of the Arimoto algorithm. By analyzing the Taylor expansion of the defining function of the Arimoto algorithm, we will clarify t…
On the Search Algorithm for the Output Distribution that Achieves the Channel Capacity
Kenji Nakagawa, Kohei Watabe, Takuto Sabu
We consider a search algorithm for the output distribution that achieves the channel capacity of a discrete memoryless channel. We will propose an algorithm by iterated projections…