Polynomial Learnability of Probabilistic Concepts with Respect to the Kullback-Leibler Divergence. - Naoki Abe; Manfred K. Warmuth; Jun'ichi Takeuchi (COLT, 1991)

Some Improved Sample Complexity Bounds in the Probabilistic PAC Learning Model. - Jun'ichi Takeuchi (ALT, 1992)

The "lob-pass" Problem and an On-line Learning Model of Rational Choice. - Naoki Abe; Jun'ichi Takeuchi (COLT, 1993)

Improved Sample Complexity Bounds for Parameter Estimation. - Jun'ichi Takeuchi (IEICE Trans. Inf. Syst., 1995)

Efficient Distribution-Free Population Learning of Simple Concepts. - Atsuyoshi Nakamura; Jun'ichi Takeuchi; Naoki Abe (Ann. Math. Artif. Intell., 1998)

The Lob-Pass Problem. - Jun'ichi Takeuchi; Naoki Abe; Shun-ichi Amari (J. Comput. Syst. Sci., 2000)

Discovering outlier filtering rules from unlabeled data: combining a supervised learner with an unsupervised learner. - Kenji Yamanishi; Jun'ichi Takeuchi (KDD, 2001)

A unifying framework for detecting outliers and change points from non-stationary time series data. - Kenji Yamanishi; Jun'ichi Takeuchi (KDD, 2002)

Distributed cooperative mining for information consortia. - Satoshi Morinaga; Kenji Yamanishi; Jun'ichi Takeuchi (KDD, 2003)

Mining traffic data from probe-car system for travel time prediction. - Takayuki Nakata; Jun'ichi Takeuchi (KDD, 2004)

On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms. - Kenji Yamanishi; Jun'ichi Takeuchi; Graham J. Williams; Peter Milne (Data Min. Knowl. Discov., 2004)

α-parallel prior and its properties. - Jun'ichi Takeuchi; Shun-ichi Amari (IEEE Trans. Inf. Theory, 2005)

A Unifying Framework for Detecting Outliers and Change Points from Time Series. - Jun'ichi Takeuchi; Kenji Yamanishi (IEEE Trans. Knowl. Data Eng., 2006)

Exponential Curvature of Markov Models. - Jun'ichi Takeuchi; Tsutomu Kawabata (ISIT, 2007)

An Incident Analysis System NICTER and Its Analysis Engines Based on Data Mining Techniques. - Daisuke Inoue; Katsunari Yoshioka; Masashi Eto; Masaya Yamagata; Eisuke Nishino; Jun'ichi Takeuchi; Kazuya Ohkouchi; Koji Nakao (ICONIP (1), 2008)

Fisher information determinant and stochastic complexity for Markov models. - Jun'ichi Takeuchi (ISIT, 2009)

A note on model selection for small sample regression. - Masanori Kawakita; Yoko Oie; Jun'ichi Takeuchi (ISITA, 2010)

Stochastic interpretation of universal portfolio and generalized target classes. - Mariko Tsurusaki; Jun'ichi Takeuchi (ISIT, 2011)

Acceleration technique for boosting classification and its application to face detection. - Masanori Kawakita; Ryota Izumi; Jun'ichi Takeuchi; Yi Hu; Tetsuya Takamori; Hirokazu Kameyama (ACML, 2011)

Information Theoretic Limit of Single-Frame Super-Resolution. - Kotaro Yamaguchi; Masanori Kawakita; Norikazu Takahashi; Jun'ichi Takeuchi (EST, 2012)

Botnet Detection Based on Non-negative Matrix Factorization and the MDL Principle. - Sayaka Yamauchi; Masanori Kawakita; Jun'ichi Takeuchi (ICONIP (5), 2012)

Constant Markov Portfolio and its application to universal portfolio with side information. - Mariko Tsurusaki; Jun'ichi Takeuchi (ISIT, 2012)

A Behavior-Based Detection Method for Outbreaks of Low-Rate Attacks. - Yaokai Feng; Yoshiaki Hori; Kouichi Sakurai; Jun'ichi Takeuchi (SAINT, 2012)

Boundedness of modified multiplicative updates for nonnegative matrix factorization. - Jiro Katayama; Norikazu Takahashi; Jun'ichi Takeuchi (CAMSAP, 2013)

Asymptotically minimax regret by Bayes mixtures for non-exponential families. - Jun'ichi Takeuchi; Andrew R. Barron (ITW, 2013)

A Behavior-based Method for Detecting Distributed Scan Attacks in Darknets. - Yaokai Feng; Yoshiaki Hori; Kouichi Sakurai; Jun'ichi Takeuchi (J. Inf. Process., 2013)

Properties of Jeffreys Mixture for Markov Sources. - Jun'ichi Takeuchi; Tsutomu Kawabata; Andrew R. Barron (IEEE Trans. Inf. Theory, 2013)

Asymptotically minimax regret for models with hidden variables. - Jun'ichi Takeuchi; Andrew R. Barron (ISIT, 2014)

Stochastic Complexity for tree models. - Jun'ichi Takeuchi; Andrew R. Barron (ITW, 2014)

Safe semi-supervised learning based on weighted likelihood. - Masanori Kawakita; Jun'ichi Takeuchi (Neural Networks, 2014)

Least Squares Superposition Codes With Bernoulli Dictionary are Still Reliable at Rates up to Capacity. - Yoshinari Takeishi; Masanori Kawakita; Jun'ichi Takeuchi (IEEE Trans. Inf. Theory, 2014)

Barron and Cover's Theory in Supervised Learning and its Application to Lasso. - Masanori Kawakita; Jun'ichi Takeuchi (ICML, 2016)

Botnet Detection Using Graphical Lasso with Graph Density. - Chansu Han; Kento Kono; Shoma Tanaka; Masanori Kawakita; Jun'ichi Takeuchi (ICONIP (1), 2016)

MDL Criterion for NMF with Application to Botnet Detection. - Shoma Tanaka; Yuki Kawamura; Masanori Kawakita; Noboru Murata; Jun'ichi Takeuchi (ICONIP (1), 2016)

An improved upper bound on block error probability of least squares superposition codes with unbiased Bernoulli dictionary. - Yoshinari Takeishi; Jun'ichi Takeuchi (ISIT, 2016)

Information geometry of the family of Markov kernels defined by a context tree. - Jun'ichi Takeuchi; Hiroshi Nagaoka (ITW, 2017)

A note on model selection for small sample regression. - Masanori Kawakita; Jun'ichi Takeuchi (Mach. Learn., 2017)

Asymptotic Behavior of Typical Sets and the Smallest High Probability Set. - Munenori Eto; Masanori Kawakita; Jun'ichi Takeuchi (ISITA, 2018)

A unified global convergence analysis of multiplicative update rules for nonnegative matrix factorization. - Norikazu Takahashi; Jiro Katayama; Masato Seki; Jun'ichi Takeuchi (Comput. Optim. Appl., 2018)

An Improved Analysis of Least Squares Superposition Codes with Bernoulli Dictionary. - Yoshinari Takeishi; Jun'ichi Takeuchi (CoRR, 2018)

A Fast Algorithm for Constructing Phylogenetic Trees with Application to IoT Malware Clustering. - Tianxiang He; Chansu Han; Ryoichi Isawa; Takeshi Takahashi 001; Shuji Kijima; Jun'ichi Takeuchi; Koji Nakao (ICONIP (1), 2019)

Improved MDL Estimators Using Local Exponential Family Bundles Applied to Mixture Families. - Kohei Miyamoto; Andrew R. Barron; Jun'ichi Takeuchi (ISIT, 2019)

Dynamics of Damped Approximate Message Passing Algorithms. - Kazushi Mimura; Jun'ichi Takeuchi (ITW, 2019)

Real-Time Detection of Malware Activities by Analyzing Darknet Traffic Using Graphical Lasso. - Chansu Han; Jumpei Shimamura; Takeshi Takahashi 001; Daisuke Inoue; Masanori Kawakita; Jun'ichi Takeuchi; Koji Nakao (TrustCom/BigDataSE, 2019)

On MDL Estimation for Simple Contaminated Gaussian Location Families. - Kohei Miyamoto; Jun'ichi Takeuchi (ISITA, 2020)

Real-Time Detection of Global Cyberthreat Based on Darknet by Estimating Anomalous Synchronization Using Graphical Lasso. - Chansu Han; Jumpei Shimamura; Takeshi Takahashi 001; Daisuke Inoue; Jun'ichi Takeuchi; Koji Nakao (IEICE Trans. Inf. Syst., 2020)

Minimum Description Length Principle in Supervised Learning With Application to Lasso. - Masanori Kawakita; Jun'ichi Takeuchi (IEEE Trans. Inf. Theory, 2020)

Which Packet Did They Catch? Associating NIDS Alerts with Their Communication Sessions. - Ryosuke Ishibashi; Hiroki Goto; Chansu Han; Tao Ban; Takeshi Takahashi 001; Jun'ichi Takeuchi (AsiaJCIS, 2021)

Scalable and Fast Hierarchical Clustering of IoT Malware Using Active Data Selection. - Tianxiang He; Chansu Han; Takeshi Takahashi 001; Shuji Kijima; Jun'ichi Takeuchi (FMEC, 2021)

Designing Comprehensive Cyber Threat Analysis Platform: Can We Orchestrate Analysis Engines? - Takeshi Takahashi 001; Yuki Umemura; Chansu Han; Tao Ban; Keisuke Furumoto; Ohnori Nakamura; Katsunari Yoshioka; Jun'ichi Takeuchi; Noboru Murata; Yoshiaki Shiraishi (PerCom Workshops, 2021)

Investigating behavioral differences between IoT malware via function call sequence graphs. - Reo Kawasoe; Chansu Han; Ryoichi Isawa; Takeshi Takahashi 001; Jun'ichi Takeuchi (SAC, 2021)

Automated Detection of Malware Activities Using Nonnegative Matrix Factorization. - Chansu Han; Jun'ichi Takeuchi; Takeshi Takahashi 001; Daisuke Inoue (TrustCom, 2021)

Leveraging Machine Learning Techniques to Identify Deceptive Decoy Documents Associated With Targeted Email Attacks. - Bo Sun; Tao Ban; Chansu Han; Takeshi Takahashi 001; Katsunari Yoshioka; Jun'ichi Takeuchi; Abdolhossein Sarrafzadeh; Meikang Qiu; Daisuke Inoue (IEEE Access, 2021)

Poster: Flexible Function Estimation of IoT Malware Using Graph Embedding Technique. - Kei Oshio; Satoshi Takada; Chansu Han; Akira Tanaka; Jun'ichi Takeuchi (ISCC, 2022)

On Fisher Information Matrix for Simple Neural Networks with Softplus Activation. - Masazumi Iida; Yoshinari Takeishi; Jun'ichi Takeuchi (ISIT, 2022)

Malicious Packet Classification Based on Neural Network Using Kitsune Features. - Kohei Miyamoto; Hiroki Goto; Ryosuke Ishibashi; Chansu Han; Tao Ban; Takeshi Takahashi 001; Jun'ichi Takeuchi (ISPR, 2022)

Dark-TRACER: Early Detection Framework for Malware Activity Based on Anomalous Spatiotemporal Patterns. - Chansu Han; Jun'ichi Takeuchi; Takeshi Takahashi 001; Daisuke Inoue (IEEE Access, 2022)

Generating Labeled Training Datasets Towards Unified Network Intrusion Detection Systems. - Ryosuke Ishibashi; Kohei Miyamoto; Chansu Han; Tao Ban; Takeshi Takahashi 001; Jun'ichi Takeuchi (IEEE Access, 2022)

Packet-Level Intrusion Detection Using LSTM Focusing on Personal Information and Payloads. - Shota Kawanaka; Yoshikatsu Kashiwabara; Kohei Miyamoto; Masazumi Iida; Chansu Han; Tao Ban; Takeshi Takahashi 001; Jun'ichi Takeuchi (AsiaJCIS, 2023)

Work in Progress: New Seed Set Selection Method of the Scalable Method for Constructing Phylogenetic Trees. - Tianxiang He; Chansu Han; Akira Tanaka; Takeshi Takahashi 001; Jun'ichi Takeuchi (CF, 2023)

Towards Functional Analysis of IoT Malware Using Function Call Sequence Graphs and Clustering. - Kei Oshio; Satoshi Takada; Tianxiang He; Chansu Han; Akira Tanaka; Takeshi Takahashi 001; Jun'ichi Takeuchi (COMPSAC, 2023)

Towards Long-Term Continuous Tracing of Internet-Wide Scanning Campaigns Based on Darknet Analysis. - Chansu Han; Akira Tanaka; Jun'ichi Takeuchi; Takeshi Takahashi 001; Tomohiro Morikawa; Tsung-Nan Lin (ICISSP, 2023)

Scalable and Fast Algorithm for Constructing Phylogenetic Trees With Application to IoT Malware Clustering. - Tianxiang He; Chansu Han; Ryoichi Isawa; Takeshi Takahashi 001; Shuji Kijima; Jun'ichi Takeuchi (IEEE Access, 2023)

Consolidating Packet-Level Features for Effective Network Intrusion Detection: A Novel Session-Level Approach. - Kohei Miyamoto; Masazumi Iida; Chansu Han; Tao Ban; Takeshi Takahashi 001; Jun'ichi Takeuchi (IEEE Access, 2023)

Improved MDL Estimators Using Fiber Bundle of Local Exponential Families for Non-exponential Families. - Kohei Miyamoto; Andrew R. Barron; Jun'ichi Takeuchi (CoRR, 2023)

Approximate spectral decomposition of Fisher information matrix for simple ReLU networks. - Yoshinari Takeishi; Masazumi Iida; Jun'ichi Takeuchi (Neural Networks, 2023)

Mitigate: Toward Comprehensive Research and Development for Analyzing and Combating IoT Malware. - Koji Nakao; Katsunari Yoshioka; Takayuki Sasaki; Rui Tanabe; Xuping Huang; Takeshi Takahashi 001; Akira Fujita; Jun'ichi Takeuchi; Noboru Murata; Junji Shikata; Kazuki Iwamoto; Kazuki Takada; et al. (IEICE Trans. Inf. Syst., 2023)

Brain Tumor Classification using Under-Sampled k-Space Data: A Deep Learning Approach. - Tania Sultana; Sho Kurosaki; Yutaka Jitsumatsu; Shigehide Kuhara; Jun'ichi Takeuchi (IEICE Trans. Inf. Syst., 2023)

Intrusion Detection Simplified: A Feature-free Approach to Traffic Classification Using Transformers. - Kohei Miyamoto; Chansu Han; Tao Ban; Takeshi Takahashi 001; Jun'ichi Takeuchi (ACSAC Workshops, 2024)

Risk Bound on MDL Estimator for Simple ReLU Networks. - Yoshinari Takeishi; Jun'ichi Takeuchi (ISIT, 2024)

Asymptotically Minimax Regret by Bayes Mixtures. - Jun'ichi Takeuchi; Andrew R. Barron (CoRR, 2024)

Risk Bounds on MDL Estimators for Linear Regression Models with Application to Simple ReLU Neural Networks. - Yoshinari Takeishi; Jun'ichi Takeuchi (CoRR, 2024)

Sparse Superposition Codes with Binomial Dictionary are Capacity-Achieving with Maximum Likelihood Decoding. - Yoshinari Takeishi; Jun'ichi Takeuchi (CoRR, 2025)

Function Forms of Simple ReLU Networks with Random Hidden Weights. - Ka Long Keith Ho; Yoshinari Takeishi; Jun'ichi Takeuchi (CoRR, 2025)

Neural Tangent Kernels and Fisher Information Matrices for Simple ReLU Networks with Random Hidden Weights. - Jun'ichi Takeuchi; Yoshinari Takeishi; Noboru Murata; Kazushi Mimura; Ka Long Keith Ho; Hiroshi Nagaoka (CoRR, 2025)