An Inference Method Using Multiple Patterns and Modification of Pattern Space. - Ichiro Takeuchi; Takeshi Furuhashi (SEAL, 1996)

Acquisition of manipulative grounded symbols for integration of symbolic processing and stimulus-reaction type parallel processing. - Ichiro Takeuchi; Takeshi Furuhashi (Adv. Robotics, 1997)

A proposal of architecture for intelligent systems with manipulative grounded symbols. - Ichiro Takeuchi; Takeshi Furuhashi (KES (1), 1998)

A description of dynamic behavior of sensory/motor systems with fuzzy symbolic dynamic systems. - Ichiro Takeuchi; Takeshi Furuhashi (Artif. Life Robotics, 2000)

Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference. - Nicolas Chapados; Yoshua Bengio; Pascal Vincent; Joumana Ghosn; Charles Dugas; Ichiro Takeuchi; Linyan Meng (NIPS, 2001)

Robust Regression with Asymmetric Heavy-Tail Noise Distributions. - Ichiro Takeuchi; Yoshua Bengio; Takafumi Kanamori (Neural Comput., 2002)

Robust regression under asymmetric or/and non-constant variance error by simultaneously training conditional quantiles. - Ichiro Takeuchi; Noriyuki Yamanaka; Takeshi Furuhashi (IJCNN, 2003)

A dynamical model for the vertical vestibuloocular reflex and optokinetic response in primate. - Yutaka Hirata; Ichiro Takeuchi; Stephen M. Highstein (Neurocomputing, 2003)

Non-crossing quantile regressions by SVM. - Ichiro Takeuchi; Takeshi Furuhashi (IJCNN, 2004)

The Entire Solution Path of Kernel-based Nonparametric Conditional Quantile Estimator. - Ichiro Takeuchi; Kaname Nomura; Takafumi Kanamori (IJCNN, 2006)

Conditional mean estimation under asymmetric and heteroscedastic error by linear combination of quantile regressions. - Takafumi Kanamori; Ichiro Takeuchi (Comput. Stat. Data Anal., 2006)

Nonparametric Quantile Estimation. - Ichiro Takeuchi; Quoc V. Le; Tim D. Sears; Alexander J. Smola (J. Mach. Learn. Res., 2006)

Reducing SVR Support Vectors by Using Backward Deletion. - Masayuki Karasuyama; Ichiro Takeuchi; Ryohei Nakano (KES (3), 2008)

A Bayesian Graph Clustering Approach Using the Prior Based on Degree Distribution. - Naoyuki Harada; Yuta Ishikawa; Ichiro Takeuchi; Ryohei Nakano (ICONIP (1), 2009)

Variational Bayes from the Primitive Initial Point for Gaussian Mixture Estimation. - Yuta Ishikawa; Ichiro Takeuchi; Ryohei Nakano (ICONIP (1), 2009)

A Density-ratio Framework for Statistical Data Processing. - Masashi Sugiyama; Takafumi Kanamori; Taiji Suzuki; Shohei Hido; Jun Sese; Ichiro Takeuchi; Liwei Wang 001 (IPSJ Trans. Comput. Vis. Appl., 2009)

Adaptive Kernel Quantile Regression for Anomaly Detection. - Hiroyuki Moriguchi; Ichiro Takeuchi; Masayuki Karasuyama; Shin-ichi Horikawa; Yoshikatsu Ohta; Tetsuji Kodama; Hiroshi Naruse (J. Adv. Comput. Intell. Intell. Informatics, 2009)

Nonparametric Conditional Density Estimation Using Piecewise-Linear Solution Path of Kernel Quantile Regression. - Ichiro Takeuchi; Kaname Nomura; Takafumi Kanamori (Neural Comput., 2009)

Efficient Leave-m-out Cross-Validation of Support Vector Regression by Generalizing Decremental Algorithm. - Masayuki Karasuyama; Ichiro Takeuchi; Ryohei Nakano (New Gener. Comput., 2009)

Detecting differentially aberrant genomic regions in multi-sample array CGH experiments using nearest-neighbor multivariate test. - Yuta Ishikawa; Ichiro Takeuchi (IJCNN, 2010)

Nonlinear regularization path for the modified Huber loss Support Vector Machines. - Masayuki Karasuyama; Ichiro Takeuchi (IJCNN, 2010)

Least-Squares Conditional Density Estimation. - Masashi Sugiyama; Ichiro Takeuchi; Taiji Suzuki; Takafumi Kanamori; Hirotaka Hachiya; Daisuke Okanohara (IEICE Trans. Inf. Syst., 2010)

Differentially Aberrant Region Detection in Array CGH Data Based on Nearest Neighbor Classification Performance. - Yuta Ishikawa; Ichiro Takeuchi (Inf. Media Technol., 2010)

Conditional Density Estimation via Least-Squares Density Ratio Estimation. - Masashi Sugiyama; Ichiro Takeuchi; Taiji Suzuki; Takafumi Kanamori; Hirotaka Hachiya; Daisuke Okanohara (AISTATS, 2010)

Multi-directional search from the primitive initial point for Gaussian mixture estimation using variational Bayes method. - Yuta Ishikawa; Ichiro Takeuchi; Ryohei Nakano (Neural Networks, 2010)

Multiple incremental decremental learning of support vector machines. - Masayuki Karasuyama; Ichiro Takeuchi (IEEE Trans. Neural Networks, 2010)

Suboptimal Solution Path Algorithm for Support Vector Machine. - Masayuki Karasuyama; Ichiro Takeuchi (ICML, 2011)

Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification. - Ichiro Takeuchi; Masashi Sugiyama (NIPS, 2011)

Nonlinear Regularization Path for Quadratic Loss Support Vector Machines. - Masayuki Karasuyama; Ichiro Takeuchi (IEEE Trans. Neural Networks, 2011)

Multi-parametric solution-path algorithm for instance-weighted support vector machines. - Masayuki Karasuyama; Naoyuki Harada; Masashi Sugiyama; Ichiro Takeuchi (Mach. Learn., 2012)

Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines. - Kohei Ogawa; Motoki Imamura; Ichiro Takeuchi; Masashi Sugiyama (ICML (3), 2013)

Safe Screening of Non-Support Vectors in Pathwise SVM Computation. - Kohei Ogawa; Yoshiki Suzuki; Ichiro Takeuchi (ICML (3), 2013)

Development and Clinical Study of Mobile 12-Lead Electrocardiography Based on Cloud Computing for Cardiac Emergency. - Hideo Fujita; Yuji Uchimura; Kayo Waki; Koji Omae; Ichiro Takeuchi; Kazuhiko Ohe (MedInfo, 2013)

Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering. - Shinichi Nakajima; Akiko Takeda; S. Derin Babacan; Masashi Sugiyama; Ichiro Takeuchi (NIPS, 2013)

Parametric Task Learning. - Ichiro Takeuchi; Tatsuya Hongo; Masashi Sugiyama; Shinichi Nakajima (NIPS, 2013)

Discovering combinatorial interactions in survival data. - David duVerle; Ichiro Takeuchi; Yuko Murakami-Tonami; Kenji Kadomatsu; Koji Tsuda (Bioinform., 2013)

Density-Difference Estimation. - Masashi Sugiyama; Takafumi Kanamori; Taiji Suzuki; Marthinus Christoffel du Plessis; Song Liu 002; Ichiro Takeuchi (Neural Comput., 2013)

Outlier Path: A Homotopy Algorithm for Robust SVM. - Shinya Suzumura; Kohei Ogawa; Masashi Sugiyama; Ichiro Takeuchi (ICML, 2014)

Quantitative analysis of time-course development of motion sickness caused by in-vehicle video watching. - Naoki Isu; Takuya Hasegawa; Ichiro Takeuchi; Akihiro Morimoto (Displays, 2014)

Quick Sensitivity Analysis for Incremental Data Modification and Its Application to Leave-one-out CV in Linear Classification Problems. - Shota Okumura; Yoshiki Suzuki; Ichiro Takeuchi (KDD, 2015)

Regularization Path of Cross-Validation Error Lower Bounds. - Atsushi Shibagaki; Yoshiki Suzuki; Masayuki Karasuyama; Ichiro Takeuchi (NIPS, 2015)

Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization. - Toshiyuki Takada; Hiroyuki Hanada; Yoshiji Yamada; Jun Sakuma; Ichiro Takeuchi (ACML, 2016)

Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling. - Atsushi Shibagaki; Masayuki Karasuyama; Kohei Hatano; Ichiro Takeuchi (ICML, 2016)

Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. - Kazuya Nakagawa; Shinya Suzumura; Masayuki Karasuyama; Koji Tsuda; Ichiro Takeuchi (KDD, 2016)

Efficiently Bounding Optimal Solutions after Small Data Modification in Large-Scale Empirical Risk Minimization. - Hiroyuki Hanada; Atsushi Shibagaki; Jun Sakuma; Ichiro Takeuchi (CoRR, 2016)

Privacy-preserving and Optimal Interval Release for Disease Susceptibility. - Kosuke Kusano; Ichiro Takeuchi; Jun Sakuma (AsiaCCS, 2017)

Selective Inference for Sparse High-Order Interaction Models. - Shinya Suzumura; Kazuya Nakagawa; Yuta Umezu; Koji Tsuda; Ichiro Takeuchi (ICML, 2017)

Stochastic Primal Dual Coordinate Method with Non-Uniform Sampling Based on Optimality Violations. - Atsushi Shibagaki; Ichiro Takeuchi (CoRR, 2017)

Homotopy continuation approaches for robust SV classification and regression. - Shinya Suzumura; Kohei Ogawa; Masashi Sugiyama; Masayuki Karasuyama; Ichiro Takeuchi (Mach. Learn., 2017)

Efficiently Monitoring Small Data Modification Effect for Large-Scale Learning in Changing Environment. - Hiroyuki Hanada; Atsushi Shibagaki; Jun Sakuma; Ichiro Takeuchi (AAAI, 2018)

Post Selection Inference with Kernels. - Makoto Yamada; Yuta Umezu; Kenji Fukumizu; Ichiro Takeuchi (AISTATS, 2018)

Finding Discriminative Animal Behaviors from Sequential Bio-Logging Trajectory Data. - Takuto Sakuma; Kazuya Nishi; Shuhei J. Yamazaki; Koutarou D. Kimura; Sakiko Matsumoto; Ken Yoda; Ichiro Takeuchi (HCI (22), 2018)

Selecting the Best in GANs Family: a Post Selection Inference Framework. - Yao-Hung Hubert Tsai; Denny Wu; Makoto Yamada; Ruslan Salakhutdinov; Ichiro Takeuchi; Kenji Fukumizu (ICLR (Workshop), 2018)

Interval-based Prediction Uncertainty Bound Computation in Learning with Missing Values. - Hiroyuki Hanada; Toshiyuki Takada; Jun Sakuma; Ichiro Takeuchi (CoRR, 2018)

Learning sparse optimal rule fit by safe screening. - Hiroki Kato; Hiroyuki Hanada; Ichiro Takeuchi (CoRR, 2018)

AFLOW-CHULL: Cloud-Oriented Platform for Autonomous Phase Stability Analysis. - Corey Oses; Eric Gossett; David Hicks; Frisco Rose; Michael J. Mehl; Eric Perim; Ichiro Takeuchi; Stefano Sanvito; Matthias Scheffler; Yoav Lederer; Ohad Levy; Cormac Toher; et al. (J. Chem. Inf. Model., 2018)

Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction. - Vo Nguyen Le Duy; Takuto Sakuma; Taiju Ishiyama; Hiroki Toda; Kazuya Arai; Masayuki Karasuyama; Yuta Okubo; Masayuki Sunaga; Yasuo Tabei; Ichiro Takeuchi (SIGSPATIAL/GIS, 2019)

Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. - Makoto Yamada; Denny Wu; Yao-Hung Hubert Tsai; Hirofumi Ohta; Ruslan Salakhutdinov; Ichiro Takeuchi; Kenji Fukumizu (ICLR (Poster), 2019)

Safe Grid Search with Optimal Complexity. - Eugène Ndiaye; Tam Le; Olivier Fercoq; Joseph Salmon; Ichiro Takeuchi (ICML, 2019)

Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining. - Tomoki Yoshida; Ichiro Takeuchi; Masayuki Karasuyama (KDD, 2019)

Computing Full Conformal Prediction Set with Approximate Homotopy. - Eugène Ndiaye; Ichiro Takeuchi (NeurIPS, 2019)

Comparative Sequential Pattern Mining of Human Trajectory Data Collected from a Campus-wide BLE Beacon System. - Shinsuke Kajioka; Takuto Sakuma; Ichiro Takeuchi (PerCom Workshops, 2019)

Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis. - Takuto Sakuma; Kazuya Nishi; Kaoru Kishimoto; Kazuya Nakagawa; Masayuki Karasuyama; Yuta Umezu; Shinsuke Kajioka; Shuhei J. Yamazaki; Koutarou D. Kimura; Sakiko Matsumoto; Ken Yoda; Matasaburo Fukutomi; et al. (Adv. Robotics, 2019)

Multi-fidelity Bayesian Optimization with Max-value Entropy Search. - Shion Takeno; Hitoshi Fukuoka; Yuhki Tsukada; Toshiyuki Koyama; Motoki Shiga; Ichiro Takeuchi; Masayuki Karasuyama (CoRR, 2019)

Statistically Discriminative Sub-trajectory Mining. - Vo Nguyen Le Duy; Takuto Sakuma; Taiju Ishiyama; Hiroki Toda; Kazuya Nishi; Masayuki Karasuyama; Yuta Okubo; Masayuki Sunaga; Yasuo Tabei; Ichiro Takeuchi (CoRR, 2019)

Active learning for level set estimation under cost-dependent input uncertainty. - Yu Inatsu; Masayuki Karasuyama; Keiichi Inoue; Ichiro Takeuchi (CoRR, 2019)

Bayesian Active Learning for Structured Output Design. - Kota Matsui; Shunya Kusakawa; Keisuke Ando; Kentaro Kutsukake; Toru Ujihara; Ichiro Takeuchi (CoRR, 2019)

Safe Triplet Screening for Distance Metric Learning. - Tomoki Yoshida; Ichiro Takeuchi; Masayuki Karasuyama (Neural Comput., 2019)

Multi-scale Domain-adversarial Multiple-instance CNN for Cancer Subtype Classification with Unannotated Histopathological Images. - Noriaki Hashimoto; Daisuke Fukushima; Ryoichi Koga; Yusuke Takagi; Kaho Ko; Kei Kohno; Masato Nakaguro; Shigeo Nakamura; Hidekata Hontani; Ichiro Takeuchi (CVPR, 2020)

Computing Valid P-Values for Image Segmentation by Selective Inference. - Kosuke Tanizaki; Noriaki Hashimoto; Yu Inatsu; Hidekata Hontani; Ichiro Takeuchi (CVPR, 2020)

Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization. - Shion Takeno; Hitoshi Fukuoka; Yuhki Tsukada; Toshiyuki Koyama; Motoki Shiga; Ichiro Takeuchi; Masayuki Karasuyama (ICML, 2020)

Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming. - Vo Nguyen Le Duy; Hiroki Toda; Ryota Sugiyama; Ichiro Takeuchi (NeurIPS, 2020)

Bayesian Experimental Design for Finding Reliable Level Set Under Input Uncertainty. - Shogo Iwazaki; Yu Inatsu; Ichiro Takeuchi (IEEE Access, 2020)

Multi-scale domain-adversarial multiple-instance CNN for cancer subtype classification with non-annotated histopathological images. - Noriaki Hashimoto; Daisuke Fukushima; Ryoichi Koga; Yusuke Takagi; Kaho Ko; Kei Kohno; Masato Nakaguro; Shigeo Nakamura; Hidekata Hontani; Ichiro Takeuchi (CoRR, 2020)

Parametric Programming Approach for Powerful Lasso Selective Inference without Conditioning on Signs. - Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2020)

Quantifying Statistical Significance of Neural Network Representation-Driven Hypotheses by Selective Inference. - Vo Nguyen Le Duy; Shogo Iwazaki; Ichiro Takeuchi (CoRR, 2020)

Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: an application to rugby union. - Rory P. Bunker; Keisuke Fujii 001; Hiroyuki Hanada; Ichiro Takeuchi (CoRR, 2020)

More Powerful and General Selective Inference for Stepwise Feature Selection using the Homotopy Continuation Approach. - Kazuya Sugiyama; Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2020)

Active Learning of Bayesian Linear Models with High-Dimensional Binary Features by Parameter Confidence-Region Estimation. - Yu Inatsu; Masayuki Karasuyama; Keiichi Inoue; Hideki Kandori; Ichiro Takeuchi (Neural Comput., 2020)

Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions. - Yu Inatsu; Masayuki Karasuyama; Keiichi Inoue; Ichiro Takeuchi (Neural Comput., 2020)

Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives. - Yu Inatsu; Daisuke Sugita; Kazuaki Toyoura; Ichiro Takeuchi (Neural Comput., 2020)

Parametric Programming Approach for More Powerful and General Lasso Selective Inference. - Vo Nguyen Le Duy; Ichiro Takeuchi (AISTATS, 2021)

Mean-Variance Analysis in Bayesian Optimization under Uncertainty. - Shogo Iwazaki; Yu Inatsu; Ichiro Takeuchi (AISTATS, 2021)

Active Learning for Distributionally Robust Level-Set Estimation. - Yu Inatsu; Shogo Iwazaki; Ichiro Takeuchi (ICML, 2021)

More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method. - Kazuya Sugiyama; Vo Nguyen Le Duy; Ichiro Takeuchi (ICML, 2021)

Topic Analysis of Superconductivity Literature by Semantic Non-negative Matrix Factorization. - Valentin G. Stanev; Erik Skau; Ichiro Takeuchi; Boian S. Alexandrov (LSSC, 2021)

Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation. - Toshiaki Tsukurimichi; Yu Inatsu; Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2021)

Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning. - Noriaki Hashimoto; Yusuke Takagi; Hiroki Masuda; Hiroaki Miyoshi; Kei Kohno; Miharu Nagaishi; Kensaku Sato; Mai Takeuchi; Takuya Furuta; Keisuke Kawamoto; Kyohei Yamada; Mayuko Moritsubo; et al. (CoRR, 2021)

Harnessing Optoelectronic Noises in a Photonic Generative Adversarial Network (GAN). - Changming Wu; Xiaoxuan Yang 001; Heshan Yu; Ruoming Peng; Ichiro Takeuchi; Yiran Chen 001; Mo Li (CoRR, 2021)

Exact Statistical Inference for the Wasserstein Distance by Selective Inference. - Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2021)

Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference. - Ryota Sugiyama; Hiroki Toda; Vo Nguyen Le Duy; Yu Inatsu; Ichiro Takeuchi (CoRR, 2021)

Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping. - A. Gilad Kusne; Austin McDannald; Brian L. DeCost; Corey Oses; Cormac Toher; Stefano Curtarolo; Apurva Mehta; Ichiro Takeuchi (CoRR, 2021)

Bayesian Optimization for Cascade-type Multi-stage Processes. - Shunya Kusakawa; Shion Takeno; Yu Inatsu; Kentaro Kutsukake; Shogo Iwazaki; Takashi Nakano; Toru Ujihara; Masayuki Karasuyama; Ichiro Takeuchi (CoRR, 2021)

Continuation Path with Linear Convergence Rate. - Eugène Ndiaye; Ichiro Takeuchi (CoRR, 2021)

Distance metric learning for graph structured data. - Tomoki Yoshida; Ichiro Takeuchi; Masayuki Karasuyama (Mach. Learn., 2021)

Bayesian Quadrature Optimization for Probability Threshold Robustness Measure. - Shogo Iwazaki; Yu Inatsu; Ichiro Takeuchi (Neural Comput., 2021)

Fast and More Powerful Selective Inference for Sparse High-Order Interaction Model. - Diptesh Das; Vo Nguyen Le Duy; Hiroyuki Hanada; Koji Tsuda; Ichiro Takeuchi (AAAI, 2022)

Bayesian Optimization for Distributionally Robust Chance-constrained Problem. - Yu Inatsu; Shion Takeno; Masayuki Karasuyama; Ichiro Takeuchi (ICML, 2022)

Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference. - Vo Nguyen Le Duy; Shogo Iwazaki; Ichiro Takeuchi (NeurIPS, 2022)

Subtype classification of malignant lymphoma using immunohistochemical staining pattern. - Noriaki Hashimoto; Kaho Ko; Tatsuya Yokota; Kei Kohno; Masato Nakaguro; Shigeo Nakamura; Ichiro Takeuchi; Hidekata Hontani (Int. J. Comput. Assist. Radiol. Surg., 2022)

Exact Statistical Inference for Time Series Similarity using Dynamic Time Warping by Selective Inference. - Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2022)

A Low-Cost Robot Science Kit for Education with Symbolic Regression for Hypothesis Discovery and Validation. - Logan Saar; Haotong Liang; Alex Wang; Austin McDannald; Efrain Rodriguez; Ichiro Takeuchi; A. Gilad Kusne (CoRR, 2022)

Benchmarking Active Learning Strategies for Materials Optimization and Discovery. - Alex Wang; Haotong Liang; Austin McDannald; Ichiro Takeuchi; A. Gilad Kusne (CoRR, 2022)

A Confidence Machine for Sparse High-Order Interaction Model. - Diptesh Das; Eugène Ndiaye; Ichiro Takeuchi (CoRR, 2022)

Transformer-based Personalized Attention Mechanism (PersAM) for Medical Images with Clinical Records. - Yusuke Takagi; Noriaki Hashimoto; Hiroki Masuda; Hiroaki Miyoshi; Koichi Ohshima; Hidekata Hontani; Ichiro Takeuchi (CoRR, 2022)

More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming. - Vo Nguyen Le Duy; Ichiro Takeuchi (J. Mach. Learn. Res., 2022)

Bayesian Optimization for Cascade-Type Multistage Processes. - Shunya Kusakawa; Shion Takeno; Yu Inatsu; Kentaro Kutsukake; Shogo Iwazaki; Takashi Nakano; Toru Ujihara; Masayuki Karasuyama; Ichiro Takeuchi (Neural Comput., 2022)

A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy. - Shion Takeno; Hitoshi Fukuoka; Yuhki Tsukada; Toshiyuki Koyama; Motoki Shiga; Ichiro Takeuchi; Masayuki Karasuyama (Neural Comput., 2022)

Stat-DSM: Statistically Discriminative Sub-Trajectory Mining With Multiple Testing Correction. - Vo Nguyen Le Duy; Takuto Sakuma; Taiju Ishiyama; Hiroki Toda; Kazuya Arai; Masayuki Karasuyama; Yuta Okubo; Masayuki Sunaga; Hiroyuki Hanada; Yasuo Tabei; Ichiro Takeuchi (IEEE Trans. Knowl. Data Eng., 2022)

A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets. - Hideaki Ishibashi; Masayuki Karasuyama; Ichiro Takeuchi; Hideitsu Hino (AISTATS, 2023)

Valid P-Value for Deep Learning-driven Salient Region. - Daiki Miwa; Vo Nguyen Le Duy; Ichiro Takeuchi (ICLR, 2023)

Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping. - Joshua Butke; Noriaki Hashimoto; Ichiro Takeuchi; Hiroaki Miyoshi; Koichi Ohshima; Jun Sakuma (MLMI@MICCAI (2), 2023)

Distributionally Robust Multi-objective Bayesian Optimization under Uncertain Environments. - Yu Inatsu; Ichiro Takeuchi (CoRR, 2023)

Latent Reconstruction-Aware Variational Autoencoder. - Onur Boyar; Ichiro Takeuchi (CoRR, 2023)

Adaptive Defective Area Identification in Material Surface Using Active Transfer Learning-based Level Set Estimation. - Shota Hozumi; Kentaro Kutsukake; Kota Matsui; Shunya Kusakawa; Toru Ujihara; Ichiro Takeuchi (CoRR, 2023)

Human-In-the-Loop for Bayesian Autonomous Materials Phase Mapping. - Felix Adams; Austin McDannald; Ichiro Takeuchi; A. Gilad Kusne (CoRR, 2023)

Bounded P-values in Parametric Programming-based Selective Inference. - Tomohiro Shiraishi; Daiki Miwa; Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2023)

Multi-Objective Bayesian Optimization with Active Preference Learning. - Ryota Ozaki 003; Kazuki Ishikawa 003; Youhei Kanzaki; Shinya Suzuki; Shion Takeno; Ichiro Takeuchi; Masayuki Karasuyama (CoRR, 2023)

Selective Inference for Changepoint detection by Recurrent Neural Network. - Tomohiro Shiraishi; Daiki Miwa; Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2023)

Multi-agent statistical discriminative sub-trajectory mining and an application to NBA basketball. - Rory P. Bunker; Vo Nguyen Le Duy; Yasuo Tabei; Ichiro Takeuchi; Keisuke Fujii 001 (CoRR, 2023)

Safe RuleFit: Learning Optimal Sparse Rule Model by Meta Safe Screening. - Hiroki Kato; Hiroyuki Hanada; Ichiro Takeuchi (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Root-finding approaches for computing conformal prediction set. - Eugène Ndiaye; Ichiro Takeuchi (Mach. Learn., 2023)

Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning. - Noriaki Hashimoto; Yusuke Takagi; Hiroki Masuda; Hiroaki Miyoshi; Kei Kohno; Miharu Nagaishi; Kensaku Sato; Mai Takeuchi; Takuya Furuta; Keisuke Kawamoto; Kyohei Yamada; Mayuko Moritsubo; et al. (Medical Image Anal., 2023)

Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications. - Hiroyuki Hanada; Noriaki Hashimoto; Kouichi Taji; Ichiro Takeuchi (Neural Comput., 2023)

Efficient model selection for predictive pattern mining model by safe pattern pruning. - Takumi Yoshida; Hiroyuki Hanada; Kazuya Nakagawa; Kouichi Taji; Koji Tsuda; Ichiro Takeuchi (Patterns, 2023)

Multi-Objective Bayesian Optimization with Active Preference Learning. - Ryota Ozaki 003; Kazuki Ishikawa 003; Youhei Kanzaki; Shion Takeno; Ichiro Takeuchi; Masayuki Karasuyama (AAAI, 2024)

CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference. - Vo Nguyen Le Duy; Hsuan-Tien Lin; Ichiro Takeuchi (AISTATS, 2024)

Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty. - Yu Inatsu; Shion Takeno; Hiroyuki Hanada; Kazuki Iwata; Ichiro Takeuchi (AISTATS, 2024)

Statistical Test for Attention Maps in Vision Transformers. - Tomohiro Shiraishi; Daiki Miwa; Teruyuki Katsuoka; Vo Nguyen Le Duy; Kouichi Taji; Ichiro Takeuchi (ICML, 2024)

Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds. - Shion Takeno; Yu Inatsu; Masayuki Karasuyama; Ichiro Takeuchi (ICML, 2024)

Modification of DDIM Encoding for Generating Counterfactual Pathology Images of Malignant Lymphoma. - Ryoichi Koga; Mauricio Kugler; Tatsuya Yokota; Kouichi Ohshima; Hiroaki Miyoshi; Miharu Nagaishi; Noriaki Hashimoto; Ichiro Takeuchi; Hidekata Hontani (VISIGRAPP (2): VISAPP, 2024)

Statistical Test for Attention Map in Vision Transformer. - Tomohiro Shiraishi; Daiki Miwa; Teruyuki Katsuoka; Vo Nguyen Le Duy; Kouichi Taji; Ichiro Takeuchi (CoRR, 2024)

Co-orchestration of Multiple Instruments to Uncover Structure-Property Relationships in Combinatorial Libraries. - Boris N. Slautin; Utkarsh Pratiush; Ilia N. Ivanov; Yongtao Liu; Rohit Pant; Xiaohang Zhang; Ichiro Takeuchi; Maxim A. Ziatdinov; Sergei V. Kalinin (CoRR, 2024)

Statistical Test for Anomaly Detections by Variational Auto-Encoders. - Daiki Miwa; Tomohiro Shiraishi; Vo Nguyen Le Duy; Teruyuki Katsuoka; Ichiro Takeuchi (CoRR, 2024)

Statistical Test for Generated Hypotheses by Diffusion Models. - Teruyuki Katsuoka; Tomohiro Shiraishi; Daiki Miwa; Vo Nguyen Le Duy; Ichiro Takeuchi (CoRR, 2024)

Distributionally Robust Safe Screening. - Hiroyuki Hanada; Satoshi Akahane; Tatsuya Aoyama; Tomonari Tanaka; Yoshito Okura; Yu Inatsu; Noriaki Hashimoto; Taro Murayama; Hanju Lee; Shinya Kojima; Ichiro Takeuchi (CoRR, 2024)

Distributionally Robust Safe Sample Screening. - Hiroyuki Hanada; Tatsuya Aoyama; Satoshi Akahane; Tomonari Tanaka; Yoshito Okura; Yu Inatsu; Noriaki Hashimoto; Shion Takeno; Taro Murayama; Hanju Lee; Shinya Kojima; Ichiro Takeuchi (CoRR, 2024)

Statistical Test for Data Analysis Pipeline by Selective Inference. - Tomohiro Shiraishi; Tatsuya Matsukawa; Shuichi Nishino; Ichiro Takeuchi (CoRR, 2024)

SANE: Strategic Autonomous Non-Smooth Exploration for Multiple Optima Discovery in Multi-modal and Non-differentiable Black-box Functions. - Arpan Biswas; Rama K. Vasudevan; Rohit Pant; Ichiro Takeuchi; Hiroshi Funakubo; Yongtao Liu (CoRR, 2024)

Statistical testing on generative AI anomaly detection tools in Alzheimer's Disease diagnosis. - Rosemary He; Ichiro Takeuchi (CoRR, 2024)

Real-time experiment-theory closed-loop interaction for autonomous materials science. - Haotong Liang; Chuangye Wang; Heshan Yu; Dylan Kirsch; Rohit Pant; Austin McDannald; A. Gilad Kusne; Ji-Cheng Zhao; Ichiro Takeuchi (CoRR, 2024)

Conditional Latent Space Molecular Scaffold Optimization for Accelerated Molecular Design. - Onur Boyar; Hiroyuki Hanada; Ichiro Takeuchi (CoRR, 2024)

Reward driven workflows for unsupervised explainable analysis of phases and ferroic variants from atomically resolved imaging data. - Kamyar Barakati; Yu Liu; Chris Nelson; Maxim A. Ziatdinov; Xiaohang Zhang; Ichiro Takeuchi; Sergei V. Kalinin (CoRR, 2024)

Automated Materials Discovery Platform Realized: Scanning Probe Microscopy of Combinatorial Libraries. - Yu Liu; Rohit Pant; Ichiro Takeuchi; R. Jackson Spurling; Jon-Paul Maria; Maxim A. Ziatdinov; Sergei V. Kalinin (CoRR, 2024)

Latent Space Bayesian Optimization With Latent Data Augmentation for Enhanced Exploration. - Onur Boyar; Ichiro Takeuchi (Neural Comput., 2024)

Selective Inference for Change Point Detection by Recurrent Neural Network. - Tomohiro Shiraishi; Daiki Miwa; Vo Nguyen Le Duy; Ichiro Takeuchi (Neural Comput., 2024)

Active Learning for Level Set Estimation Using Randomized Straddle Algorithms. - Yu Inatsu; Shion Takeno; Kentaro Kutsukake; Ichiro Takeuchi (Trans. Mach. Learn. Res., 2024)

Statistical Test for Auto Feature Engineering by Selective Inference. - Tatsuya Matsukawa; Tomohiro Shiraishi; Shuichi Nishino; Teruyuki Katsuoka; Ichiro Takeuchi (AISTATS, 2025)

Crystal-LSBO: Automated Design of De Novo Crystals With Latent Space Bayesian Optimization. - Onur Boyar; Yanheng Gu; Yuji Tanaka; Shunsuke Tonogai; Tomoya Itakura; Ichiro Takeuchi (Neural Comput., 2025)

Distributionally Robust Coreset Selection under Covariate Shift. - Tomonari Tanaka; Hiroyuki Hanada; Hanting Yang; Tatsuya Aoyama; Yu Inatsu; Satoshi Akahane; Yoshito Okura; Noriaki Hashimoto; Taro Murayama; Hanju Lee; Shinya Kojima; Ichiro Takeuchi (Trans. Mach. Learn. Res., 2025)

Change Point Detection in the Frequency Domain with Statistical Reliability. - Akifumi Yamada; Tomohiro Shiraishi; Shuichi Nishino; Teruyuki Katsuoka; Kouichi Taji; Ichiro Takeuchi (Trans. Mach. Learn. Res., 2025)

si4onnx: A Python package for Selective Inference in Deep Learning Models. - Teruyuki Katsuoka; Tomohiro Shiraishi; Daiki Miwa; Shuichi Nishino; Ichiro Takeuchi (CoRR, 2025)

AI-Accelerated Electronic Materials Discovery and Development. - Christopher C. Price; Ichiro Takeuchi; James M. Rondinelli; Wei Chen 041; Christopher L. Hinkle (Computer, 2025)

Time Series Anomaly Detection in the Frequency Domain with Statistical Reliability. - Akifumi Yamada; Tomohiro Shiraishi; Shuichi Nishino; Teruyuki Katsuoka; Kouichi Taji; Ichiro Takeuchi (CoRR, 2025)

Bayesian Optimization for Simultaneous Selection of Machine Learning Algorithms and Hyperparameters on Shared Latent Space. - Kazuki Ishikawa 003; Ryota Ozaki 003; Yohei Kanzaki; Ichiro Takeuchi; Masayuki Karasuyama (CoRR, 2025)

Generalized Kernel Inducing Points by Duality Gap for Dataset Distillation. - Tatsuya Aoyama; Hanting Yang; Hiroyuki Hanada; Satoshi Akahane; Tomonari Tanaka; Yoshito Okura; Yu Inatsu; Noriaki Hashimoto; Taro Murayama; Hanju Lee; Shinya Kojima; Ichiro Takeuchi (CoRR, 2025)

Statistically Significant kNNAD by Selective Inference. - Mizuki Niihori; Teruyuki Katsuoka; Tomohiro Shiraishi; Shuichi Nishino; Ichiro Takeuchi (CoRR, 2025)

Distributionally Robust Active Learning for Gaussian Process Regression. - Shion Takeno; Yoshito Okura; Yu Inatsu; Tatsuya Aoyama; Tomonari Tanaka; Satoshi Akahane; Hiroyuki Hanada; Noriaki Hashimoto; Taro Murayama; Hanju Lee; Shinya Kojima; Ichiro Takeuchi (CoRR, 2025)

Explainable Classifier for Malignant Lymphoma Subtyping via Cell Graph and Image Fusion. - Daiki Nishiyama; Hiroaki Miyoshi; Noriaki Hashimoto; Koichi Ohshima; Hidekata Hontani; Ichiro Takeuchi; Jun Sakuma (CoRR, 2025)

Rapid analysis of point-contact Andreev reflection spectra via machine learning with adaptive data augmentation. - Dongik Lee; Valentin G. Stanev; Xiaohang Zhang; Mijeong Kang; Ichiro Takeuchi; Seunghun Lee (CoRR, 2025)

Causal Discovery from Data Assisted by Large Language Models. - Kamyar Barakati; Alexander Molak; Chris Nelson; Xiaohang Zhang; Ichiro Takeuchi; Sergei V. Kalinin (CoRR, 2025)

Statistical Test for Saliency Maps of Graph Neural Networks via Selective Inference. - Shuichi Nishino; Tomohiro Shiraishi; Teruyuki Katsuoka; Ichiro Takeuchi (CoRR, 2025)

Multi-Scale Representation of Follicular Lymphoma Pathology Images in a Single Hyperbolic Space. - Kei Taguchi; Kazumasa Ohara; Tatsuya Yokota; Hiroaki Miyoshi; Noriaki Hashimoto; Ichiro Takeuchi; Hidekata Hontani (CoRR, 2025)

Regret Analysis of Posterior Sampling-Based Expected Improvement for Bayesian Optimization. - Shion Takeno; Yu Inatsu; Masayuki Karasuyama; Ichiro Takeuchi (CoRR, 2025)