Y. Kawahara

发表

Change-Point Detection in Time-Series Data by Direct Density-Ratio Estimation

Masashi Sugiyama, Yoshinobu Kawahara, Masashi Sugiyama, 2009, SDM.

Koopman Spectrum Nonlinear Regulator and Provably Efficient Online Learning pdf

Yoshinobu Kawahara, Kendall Lowrey, Motoya Ohnishi, 2021, ArXiv.

Minimum Average Cost Clustering

Satoru Iwata, Yoshinobu Kawahara, Kiyohito Nagano, 2010, NIPS.

Toxicogenomic prediction with group sparse regularization based on transcription factor network information

Yoshinobu Kawahara, Takashi Washio, Keisuke Nagata, 2015 .

Weighted Likelihood Policy Search with Model Selection

Yoshinobu Kawahara, Takashi Washio, Tsuyoshi Ueno, 2012, NIPS.

Fuel-Optimal Continuous-Thrust Guidance Algorithms for a Large Number of Formation Flying Spacecraft

Shinichi Nakasuka, Yoshinobu Kawahara, Yuichi Tsuda, 2004 .

Prediction and classification in equation-free collective motion dynamics

Yoshinobu Kawahara, Keisuke Fujii, Takeshi Kawasaki, 2018, PLoS Comput. Biol..

Analysis of factors predicting who obtains a ball in basketball rebounding situations

Yoshinobu Kawahara, Keisuke Fujii, Motokazu Hojo, 2019, International Journal of Performance Analysis in Sport.

DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model

Aapo Hyvärinen, Yoshinobu Kawahara, Patrik O. Hoyer, 2011, J. Mach. Learn. Res..

Non-Gaussian Methods for Learning Linear Structural Equation Models

Shohei Shimizu, Y. Kawahara, T. Washio, 2010 .

Data-driven spectral analysis for coordinative structures in periodic systems with unknown and redundant dynamics

Naoya Takeishi, Benio Kibushi, Motoki Kouzaki, 2019, bioRxiv.

Efficient network-guided multi-locus association mapping with graph cuts

Yoshinobu Kawahara, Karsten M. Borgwardt, Dominik Grimm, 2012, Bioinform..

A min-cut solution to mapping phenotypes to networks of genetic markers

Karsten M. Borgwardt, K. Borgwardt, Y. Kawahara, 2012 .

1 DIAGNOSIS METHOD FOR SPACECRAFT USING DYNAMIC BAYESIAN NETWORKS

Y. Kawahara, T. Yairi, K. Machida, 2005 .

Toxicogenomic prediction with graph-based structured regularization on transcription factor network

Yoshinobu Kawahara, Takashi Washio, Keisuke Nagata, 2016 .

ANALYZING RELATIONSHIPS BETWEEN CTARMA AND ARMA MODELS

Y. Kawahara, T. Washio, M. Demeshko, 2011 .

Controlling Nonlinear Dynamical Systems with Linear Quadratic Regulator-based Policy Networks in Koopman space

Y. Kawahara, Tomoharu Iwata, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

Application of Continuous and Structural ARMA modeling for noise analysis of a BWR coupled core and plant instability event

Y. Kawahara, C. Aguirre, T. Washio, 2015 .

Cognition and interpersonal coordination of patients with schizophrenia who have sports habits

Y. Kawahara, Hidehiko Takahashi, Keisuke Fujii, 2020, PloS one.

Stable Invariant Models via Koopman Spectra

Y. Kawahara, Takuya Konishi, 2022, ArXiv.

Koopman Q-learning: Offline Reinforcement Learning via Symmetries of Dynamics

Y. Kawahara, M. Weissenbacher, Samarth Sinha, 2021, ICML.

Data-driven End-to-end Learning of Pole Placement Control for Nonlinear Dynamics via Koopman Invariant Subspaces

Y. Kawahara, Tomoharu Iwata, 2022, ArXiv.

Data-driven operator-theoretic analysis of weak interactions in synchronized network dynamics

Y. Kawahara, M. Ikeda, H. Nakao, 2022, 2208.06186.

Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies

Y. Kawahara, Tomoharu Iwata, 2022, ArXiv.

Separation of stationary and non-stationary sources with a generalized eigenvalue problem

Yoshinobu Kawahara, Takashi Washio, Satoshi Hara, 2012, Neural Networks.

Analyzing Optimal Marketing Strategies Over Customers' Networks

Y. Kawahara, T. Washio, Qixin Liu, 2011 .

Higher Order Fused Regularization for Supervised Learning with Grouped Parameters

Koh Takeuchi, Tomoharu Iwata, Yoshinobu Kawahara, 2015, ECML/PKDD.

An experimental comparison of linear non-Gaussian causal discovery methods and their variants

Yoshinobu Kawahara, Takashi Washio, Shohei Shimizu, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Non-Gaussian Methods for Learning Linear Structural Equation Models

Shohei Shimizu, Y. Kawahara, T. Washio, 2010 .

A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model pdf

Aapo Hyvärinen, Yoshinobu Kawahara, Shohei Shimizu, 2009, UAI.

Prediction of Compound Bioactivities Using Heat-Diffusion Equation

Mi-Ho Giga, Yoshinobu Kawahara, Keiko Imamura, 2020, Patterns.

Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition

Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi, 2017, NIPS.

Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM pdf

Akihiro Yamamoto, Joe Suzuki, Yoshinobu Kawahara, 2014, ArXiv.

Efficient Generalized Fused Lasso and its Application to the Diagnosis of Alzheimer's Disease

Wen Gao, Yoshinobu Kawahara, Yizhou Wang, 2014, AAAI.

Parametric Maxflows for Structured Sparse Learning with Convex Relaxations of Submodular Functions pdf

Yoshinobu Kawahara, Yutaro Yamaguchi, Y. Kawahara, 2015, ArXiv.

Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis

Yoshinobu Kawahara, Y. Kawahara, 2016, NIPS.

Reproducing kernel Hilbert C*-module and kernel mean embeddings pdf

Yoshinobu Kawahara, Yuka Hashimoto, Takeshi Katsura, 2021, J. Mach. Learn. Res..

Multi-Task Feature Selection on Multiple Networks via Maximum Flows

Yoshinobu Kawahara, Karsten M. Borgwardt, Dominik Grimm, 2014, SDM.

Change-Point Detection Algorithms based on Subspace Methods

Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida, 2008 .

Change-Point Detection in Time-Series Data Based on Subspace Identification

Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida, 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).

Simultaneous pursuit of out-of-sample performance and sparsity in index tracking portfolios

Akiko Takeda, Yoshinobu Kawahara, Mahesan Niranjan, 2012, Comput. Manag. Sci..

Automatically recognizing strategic cooperative behaviors in various situations of a team sport

Yoshinobu Kawahara, Keisuke Fujii, Yuki Inaba, 2018, PloS one.

Bayesian Dynamic Mode Decomposition

Yasuo Tabei, Naoya Takeishi, Yoshinobu Kawahara, 2017, IJCAI.

Subspace dynamic mode decomposition for stochastic Koopman analysis.

Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi, 2017, Physical review. E.

Sequential change‐point detection based on direct density‐ratio estimation

Masashi Sugiyama, Yoshinobu Kawahara, Masashi Sugiyama, 2012, Stat. Anal. Data Min..

Spacecraft Diagnosis Method Using Dynamic Bayesian Networks

Yoshinobu Kawahara, Takehisa Yairi, Kazuo Machida, 2006 .

Structured Convex Optimization under Submodular Constraints pdf

Yoshinobu Kawahara, Kiyohito Nagano, Y. Kawahara, 2013, UAI.

Efficient Generalized Fused Lasso and Its Applications

Wen Gao, Yoshinobu Kawahara, Yizhou Wang, 2016, ACM Trans. Intell. Syst. Technol..

Knowledge-Based Regularization in Generative Modeling

Naoya Takeishi, Yoshinobu Kawahara, Y. Kawahara, 2020, IJCAI.

Learning Dynamics Models with Stable Invariant Sets pdf

Naoya Takeishi, Yoshinobu Kawahara, Y. Kawahara, 2020, AAAI.

euMMD: efficiently computing the MMD two-sample test statistic for univariate data

Y. Kawahara, D. Bodenham, 2023, Statistics and Computing.

A Novel Continuous and Structural VAR Modeling Approach and Its Application to Reactor Noise Analysis

Yoshinobu Kawahara, Takashi Washio, Marina Demeshko, 2015, ACM Trans. Intell. Syst. Technol..

A Novel Structural AR Modeling Approach for a Continuous Time Linear Markov System

Yoshinobu Kawahara, Takashi Washio, Marina Demeshko, 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise pdf

Yoshinobu Kawahara, Masahiro Ikeda, Isao Ishikawa, 2019, J. Mach. Learn. Res..

Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators

Keisuke Fujii, Yoshinobu Kawahara, Masahiro Ikeda, 2018, NeurIPS.

Koopman spectral analysis of elementary cellular automata.

Yoshinobu Kawahara, Yoshihiro Yamazaki, Keisuke Taga, 2021, Chaos.

Neural Dynamic Mode Decomposition for End-to-End Modeling of Nonlinear Dynamics pdf

Yoshinobu Kawahara, Tomoharu Iwata, Y. Kawahara, 2020, Journal of Computational Dynamics.

Data-driven spectral analysis for coordinative structures in periodic human locomotion

Keisuke Fujii, Naoya Takeishi, Benio Kibushi, 2019, Scientific Reports.

Physically-interpretable classification of network dynamics for complex collective motions pdf

Keisuke Fujii, Naoya Takeishi, Yoshinobu Kawahara, 2019, ArXiv.

Dynamic mode decomposition in vector-valued reproducing kernel Hilbert spaces for extracting dynamical structure among observables

Keisuke Fujii, Yoshinobu Kawahara, Y. Kawahara, 2018, Neural Networks.

Stable Invariant Models via Koopman Spectra

Y. Kawahara, Takuya Konishi, 2022, Neural networks : the official journal of the International Neural Network Society.

Learning with Coherence Patterns in Multivariate Time-series Data via Dynamic Mode Decomposition

Masashi Hiraoka, Yoshinobu Kawahara, Takehito Bito, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Supervised dynamic mode decomposition via multitask learning

Keisuke Fujii, Yoshinobu Kawahara, Y. Kawahara, 2019, Pattern Recognit. Lett..

Factorially Switching Dynamic Mode Decomposition for Koopman Analysis of Time-Variant Systems

Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Metric on Nonlinear Dynamical Systems with Koopman Operators pdf

Keisuke Fujii, Yoshinobu Kawahara, Masahiro Ikeda, 2018, NIPS 2018.

Koopman Spectral Kernels for Comparing Complex Dynamics: Application to Multiagent Sport Plays

Keisuke Fujii, Yoshinobu Kawahara, Yuki Inaba, 2017, ECML/PKDD.

Sparse nonnegative dynamic mode decomposition

Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi, 2017, 2017 IEEE International Conference on Image Processing (ICIP).

Toxicity prediction from toxicogenomic data based on class association rule mining

Yoshinobu Kawahara, Takashi Washio, Akira Unami, 2014, Toxicology reports.

An efficient branch-and-bound algorithm for submodular function maximization pdf

Shunji Umetani, Yoshinobu Kawahara, Naoya Uematsu, 2018, ArXiv.

Many-body Approximation for Non-negative Tensors

Y. Kawahara, M. Sugiyama, Kazu Ghalamkari, 2022, 2209.15338.

Representative Selection with Structured Sparsity

Junsong Yuan, Yoshinobu Kawahara, Hongxing Wang, 2017, Pattern Recognit..

Structurally Regularized Non-negative Tensor Factorization for Spatio-Temporal Pattern Discoveries

Koh Takeuchi, Tomoharu Iwata, Yoshinobu Kawahara, 2017, ECML/PKDD.

Discovering causal structures in binary exclusive-or skew acyclic models

Akihiro Yamamoto, Joe Suzuki, Yoshinobu Kawahara, 2011, UAI.

Submodular fractional programming for balanced clustering

Yoshio Okamoto, Yoshinobu Kawahara, Kiyohito Nagano, 2011, Pattern Recognit. Lett..

euMMD: efficiently computing the MMD two-sample test statistic for univariate data

Y. Kawahara, D. Bodenham, 2023, Statistics and Computing.

Size-constrained Submodular Minimization through Minimum Norm Base

Kazuyuki Aihara, Yoshinobu Kawahara, Kiyohito Nagano, 2011, ICML.

GroupLiNGAM: Linear non-Gaussian acyclic models for sets of variables pdf

Yoshinobu Kawahara, Takashi Washio, Shohei Shimizu, 2010, ArXiv.

Skill grouping method: Mining and clustering skill differences from body movement BigData

Yoshinobu Kawahara, Shinichi Yamagiwa, Yoshinobu Watanabe, 2015, 2015 IEEE International Conference on Big Data (Big Data).

Prismatic Algorithm for Discrete D.C. Programming Problem

Yoshinobu Kawahara, Takashi Washio, Y. Kawahara, 2011, NIPS.

Submodularity Cuts and Applications

Jeff A. Bilmes, Yoshinobu Kawahara, Koji Tsuda, 2009, NIPS.

Spacecraft telemetry data monitoring by dimensionality reduction techniques

Yoshinobu Kawahara, Takehisa Yairi, Noboru Takata, 2010, Proceedings of SICE Annual Conference 2010.

On Anomaly Interpretation via Shapley Values pdf

Naoya Takeishi, Yoshinobu Kawahara, Y. Kawahara, 2020, ArXiv.

Learning Non-linear Dynamical Systems by Alignment of Local Linear Models

Yoshinobu Kawahara, Takehisa Yairi, Masao Joko, 2010, 2010 20th International Conference on Pattern Recognition.

Many-body Approximation for Non-negative Tensors

Y. Kawahara, M. Sugiyama, Kazu Ghalamkari, 2022, NeurIPS.

Metric on random dynamical systems with vector-valued reproducing kernel Hilbert spaces pdf

Yoshinobu Kawahara, Masahiro Ikeda, Isao Ishikawa, 2019, ArXiv.

Variational Inference of Penalized Regression with Submodular Functions

Koh Takeuchi, Yoshinobu Kawahara, Yuichi Yoshida, 2019, UAI.

Arrangement of Low-Dimensional Parallel Coordinate Plots for High-Dimensional Data Visualization

Yoshinobu Kawahara, Takayuki Itoh, Satoshi Morinaga, 2013, 2013 17th International Conference on Information Visualisation.

Kernel Mean Embeddings of Von Neumann-Algebra-Valued Measures pdf

Yoshinobu Kawahara, Masahiro Ikeda, Isao Ishikawa, 2020, ArXiv.