Ichiro Takeuchi
42 papers · 2006–2026 · 9 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+14 more ↓ Show less ↑
π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (23) π Renaissance Researcher (7) π Interdisciplinary Bridge π£ Hot Topic Early Bird
π
Academic Marathon
(19)
πΊοΈ
Taxonomy Completionist
(23)
π
Conference Polyglot
(9)
π
Keyword Trendsetter Combo
(4)
π
Triple Crown
π
Keyword Champion
(2)
π
Grand Slam
π¬
Deep Specialist
(15)
ποΈ
Keyword Collector
(82)
π
Trend Setter
π₯
Unstoppable
(17)
π
Conference Pioneer
π
Century Club
(41)
β‘
Prolific Year
(5)
Conferences
ICML (14)
NIPS (9)
AISTATS (8)
AAAI (3)
CVPR (2)
ICLR (2)
JMLR (2)
ACML (1)
MICCAI (1)
Top co-authors
Research topics
Keywords
selective inference
(9)
bayesian optimization
(6)
parametric programming
(5)
statistical inference
(5)
support vector machine
(4)
regularization path
(4)
gaussian process
(3)
hypothesis testing
(3)
active learning
(3)
feature selection
(3)
multi-objective optimization
(3)
homotopy method
(3)
conformal prediction
(2)
quadratic programming
(2)
image segmentation
(2)
regularization parameter
(2)
quantile regression
(2)
domain adaptation
(2)
nonparametric estimation
(2)
empirical risk minimization
(2)
Papers
Statistically Robust Sparse High-order Interaction Model
AAAI 2026
Explainable Classifier for Malignant Lymphoma Subtyping via Cell Graph and Image Fusion
MICCAI 2025
Distributionally Robust Active Learning for Gaussian Process Regression
ICML 2025
Statistical Test for Feature Selection Pipelines by Selective Inference
ICML 2025
Statistical Test for Auto Feature Engineering by Selective Inference
AISTATS 2025
Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty
AISTATS 2024
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds
ICML 2024
Multi-Objective Bayesian Optimization with Active Preference Learning
AAAI 2024
Statistical Test for Attention Maps in Vision Transformers
ICML 2024
CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference
AISTATS 2024
Valid P-Value for Deep Learning-driven Salient Region
ICLR 2023
A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets
AISTATS 2023
Bayesian Optimization for Distributionally Robust Chance-constrained Problem
ICML 2022
Fast and More Powerful Selective Inference for Sparse High-Order Interaction Model
AAAI 2022
More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming
JMLR 2022
Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference
NIPS 2022
Parametric Programming Approach for More Powerful and General Lasso Selective Inference
AISTATS 2021
Active Learning for Distributionally Robust Level-Set Estimation
ICML 2021
More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method
ICML 2021
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
AISTATS 2021
Computing Valid P-Values for Image Segmentation by Selective Inference
CVPR 2020
Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming
NIPS 2020
Multi-scale Domain-adversarial Multiple-instance CNN for Cancer Subtype Classification with Unannotated Histopathological Images
CVPR 2020
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization
ICML 2020
Safe Grid Search with Optimal Complexity
ICML 2019
Computing Full Conformal Prediction Set with Approximate Homotopy
NIPS 2019
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator
ICLR 2019
Post Selection Inference with Kernels
AISTATS 2018
Selective Inference for Sparse High-Order Interaction Models
ICML 2017
Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling
ICML 2016
Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization
ACML 2016
Regularization Path of Cross-Validation Error Lower Bounds
NIPS 2015
Outlier Path: A Homotopy Algorithm for Robust SVM
ICML 2014
Infinitesimal Annealing for Training Semi-Supervised Support Vector Machines
ICML 2013
Safe Screening of Non-Support Vectors in Pathwise SVM Computation
ICML 2013
Global Solver and Its Efficient Approximation for Variational Bayesian Low-rank Subspace Clustering
NIPS 2013
Parametric Task Learning
NIPS 2013
Density-Difference Estimation
NIPS 2012
Target Neighbor Consistent Feature Weighting for Nearest Neighbor Classification
NIPS 2011
Conditional Density Estimation via Least-Squares Density Ratio Estimation
AISTATS 2010
Multiple Incremental Decremental Learning of Support Vector Machines
NIPS 2009
Nonparametric Quantile Estimation
JMLR 2006