# Yoshinobu Kawahara

According to our database

Collaborative distances:

^{1}, Yoshinobu Kawahara authored at least 65 papers between 2006 and 2020.Collaborative distances:

## Timeline

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## Bibliography

2020

Learning Dynamics Models with Stable Invariant Sets.

CoRR, 2020

On Anomaly Interpretation via Shapley Values.

CoRR, 2020

Analysis via Orthonormal Systems in Reproducing Kernel Hilbert C

^{*}-Modules and Applications.
CoRR, 2020

Dynamic Mode Decomposition via Dictionary Learning for Foreground Modeling in Videos.

Proceedings of the 15th International Joint Conference on Computer Vision, 2020

Knowledge-Based Regularization in Generative Modeling.

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

Supervised dynamic mode decomposition via multitask learning.

Pattern Recognit. Lett., 2019

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

Neural Networks, 2019

Krylov Subspace Method for Nonlinear Dynamical Systems with Random Noise.

CoRR, 2019

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

CoRR, 2019

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

CoRR, 2019

Regularizing Generative Models Using Knowledge of Feature Dependence.

CoRR, 2019

Variational Inference of Penalized Regression with Submodular Functions.

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

An Efficient Branch-and-Cut Algorithm for Approximately Submodular Function Maximization.

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

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

Proceedings of the International Joint Conference on Neural Networks, 2019

Active Change-Point Detection.

Proceedings of The 11th Asian Conference on Machine Learning, 2019

2018

Prediction and classification in equation-free collective motion dynamics.

PLoS Computational Biology, 2018

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

CoRR, 2018

Metric on Nonlinear Dynamical Systems with Koopman Operators.

CoRR, 2018

Metric on Nonlinear Dynamical Systems with Perron-Frobenius Operators.

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

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

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

Representative Selection with Structured Sparsity.

Pattern Recognit., 2017

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

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

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

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition.

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Bayesian Dynamic Mode Decomposition.

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Sparse nonnegative dynamic mode decomposition.

Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

2016

Efficient Generalized Fused Lasso and Its Applications.

ACM Trans. Intell. Syst. Technol., 2016

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

ACM Trans. Intell. Syst. Technol., 2016

Dynamic Mode Decomposition with Reproducing Kernels for Koopman Spectral Analysis.

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Scatterplot layout for high-dimensional data visualization.

J. Vis., 2015

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

CoRR, 2015

Higher Order Fused Regularization for Supervised Learning with Grouped Parameters.

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

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

Proceedings of the 2015 IEEE International Conference on Big Data, 2015

On Approximate Non-submodular Minimization via Tree-Structured Supermodularity.

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

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

CoRR, 2014

Multi-Task Feature Selection on Multiple Networks via Maximum Flows.

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Workshop on Graph-Based Algorithms for Big Data and Its Applications (GABA2014).

Proceedings of the New Frontiers in Artificial Intelligence, 2014

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

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013

Active learning for noisy oracle via density power divergence.

Neural Networks, 2013

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

Comput. Manag. Sci., 2013

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

Bioinform., 2013

Structured Convex Optimization under Submodular Constraints.

Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

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

Proceedings of the 17th International Conference on Information Visualisation, 2013

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

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

2012

Sequential change-point detection based on direct density-ratio estimation.

Statistical Analysis and Data Mining, 2012

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

Neural Networks, 2012

Weighted Likelihood Policy Search with Model Selection.

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Robust Active Learning for Linear Regression via Density Power Divergence.

Proceedings of the Neural Information Processing - 19th International Conference, 2012

2011

Submodular fractional programming for balanced clustering.

Pattern Recognit. Lett., 2011

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

J. Mach. Learn. Res., 2011

Analyzing relationships among ARMA processes based on non-Gaussianity of external influences.

Neurocomputing, 2011

Prismatic Algorithm for Discrete D.C. Programming Problems

CoRR, 2011

Discovering causal structures in binary exclusive-or skew acyclic models.

Proceedings of the UAI 2011, 2011

Prismatic Algorithm for Discrete D.C. Programming Problem.

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Size-constrained Submodular Minimization through Minimum Norm Base.

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

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

CoRR, 2010

Minimum Average Cost Clustering.

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

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

Proceedings of the International Joint Conference on Neural Networks, 2010

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

Proceedings of the 20th International Conference on Pattern Recognition, 2010

Stationary Subspace Analysis as a Generalized Eigenvalue Problem.

Proceedings of the Neural Information Processing. Theory and Algorithms, 2010

2009

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

Proceedings of the UAI 2009, 2009

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

Proceedings of the SIAM International Conference on Data Mining, 2009

Submodularity Cuts and Applications.

Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007

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

Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006

A Kernel Subspace Method by Stochastic Realization for Learning Nonlinear Dynamical Systems.

Proceedings of the Advances in Neural Information Processing Systems 19, 2006