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07/21/2023
Bounded P-values in Parametric Programming-based Selective Inference
Selective inference (SI) has been actively studied as a promising framew...
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06/23/2023
Efficient Model Selection for Predictive Pattern Mining Model by Safe Pattern Pruning
Predictive pattern mining is an approach used to construct prediction mo...
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06/22/2023
Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications
In this study, we have developed an incremental machine learning (ML) me...
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06/17/2023
Human-In-the-Loop for Bayesian Autonomous Materials Phase Mapping
Autonomous experimentation (AE) combines machine learning and research h...
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04/03/2023
Adaptive Defective Area Identification in Material Surface Using Active Transfer Learning-based Level Set Estimation
In material characterization, identifying defective areas on a material ...
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02/05/2023
Latent Reconstruction-Aware Variational Autoencoder
Variational Autoencoders (VAEs) have become increasingly popular in rece...
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01/27/2023
Distributionally Robust Multi-objective Bayesian Optimization under Uncertain Environments
In this study, we address the problem of optimizing multi-output black-b...
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01/06/2023
Valid P-Value for Deep Learning-Driven Salient Region
Various saliency map methods have been proposed to interpret and explain...
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06/07/2022
Transformer-based Personalized Attention Mechanism (PersAM) for Medical Images with Clinical Records
In medical image diagnosis, identifying the attention region, i.e., the ...
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05/28/2022
A Confidence Machine for Sparse High-Order Interaction Model
In predictive modeling for high-stake decision-making, predictors must b...
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04/12/2022
Benchmarking Active Learning Strategies for Materials Optimization and Discovery
Autonomous physical science is revolutionizing materials science. In the...
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04/08/2022
A Low-Cost Robot Science Kit for Education with Symbolic Regression for Hypothesis Discovery and Validation
The next generation of physical science involves robot scientists - auto...
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02/14/2022
Exact Statistical Inference for Time Series Similarity using Dynamic Time Warping by Selective Inference
In this paper, we study statistical inference on the similarity/distance...
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01/31/2022
Bayesian Optimization for Distributionally Robust Chance-constrained Problem
In black-box function optimization, we need to consider not only control...
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12/09/2021
Continuation Path with Linear Convergence Rate
Path-following algorithms are frequently used in composite optimization ...
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12/01/2021
Topic Analysis of Superconductivity Literature by Semantic Non-negative Matrix Factorization
We utilize a recently developed topic modeling method called SeNMFk, ext...
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11/16/2021
Bayesian Optimization for Cascade-type Multi-stage Processes
Complex processes in science and engineering are often formulated as mul...
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11/15/2021
Physics in the Machine: Integrating Physical Knowledge in Autonomous Phase-Mapping
Application of artificial intelligence (AI), and more specifically machi...
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10/18/2021
Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference
In this paper, we study statistical inference of change-points (CPs) in ...
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09/29/2021
Exact Statistical Inference for the Wasserstein Distance by Selective Inference
In this paper, we study statistical inference for the Wasserstein distan...
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07/08/2021
Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning
In the present study, we propose a novel case-based similar image retrie...
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06/09/2021
Fast and More Powerful Selective Inference for Sparse High-order Interaction Model
Automated high-stake decision-making such as medical diagnosis requires ...
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05/11/2021
More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming
Conditional selective inference (SI) has been studied intensively as a n...
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05/02/2021
Selective Inference in Propensity Score Analysis
Selective inference (post-selection inference) is a methodology that has...
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04/22/2021
Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation
In practical data analysis under noisy environment, it is common to firs...
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04/14/2021
Root-finding Approaches for Computing Conformal Prediction Set
Conformal prediction constructs a confidence set for an unobserved respo...
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02/08/2021
Active learning for distributionally robust level-set estimation
Many cases exist in which a black-box function f with high evaluation co...
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12/25/2020
More Powerful and General Selective Inference for Stepwise Feature Selection using the Homotopy Continuation Approach
Conditional Selective Inference (SI) has been actively studied as a new ...
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10/29/2020
Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: an application to rugby union
Given a set of sequences comprised of time-ordered events, sequential pa...
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10/05/2020
Quantifying Statistical Significance of Neural Network Representation-Driven Hypotheses by Selective Inference
In the past few years, various approaches have been developed to explain...
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09/17/2020
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
We consider active learning (AL) in an uncertain environment in which tr...
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06/22/2020
Bayesian Quadrature Optimization for Probability Threshold Robustness Measure
In many product development problems, the performance of the product is ...
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06/11/2020
On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning
Active learning - the field of machine learning (ML) dedicated to optima...
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04/21/2020
Parametric Programming Approach for Powerful Lasso Selective Inference without Conditioning on Signs
In the past few years, Selective Inference (SI) has been actively studie...
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03/31/2020
CRYSPNet: Crystal Structure Predictions via Neural Network
Structure is the most basic and important property of crystalline solids...
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02/21/2020
Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming
There is a vast body of literature related to methods for detecting chan...
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02/03/2020
Distance Metric Learning for Graph Structured Data
Graphs are versatile tools for representing structured data. Therefore, ...
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01/06/2020
Multi-scale domain-adversarial multiple-instance CNN for cancer subtype classification with non-annotated histopathological images
We propose a new method for cancer subtype classification from histopath...
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11/09/2019
Bayesian Active Learning for Structured Output Design
In this paper, we propose an active learning method for an inverse probl...
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10/26/2019
Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty
In the manufacturing industry, it is often necessary to repeat expensive...
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09/20/2019
Computing Full Conformal Prediction Set with Approximate Homotopy
If you are predicting the label y of a new object with ŷ, how confident ...
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09/13/2019
Active learning for level set estimation under cost-dependent input uncertainty
As part of a quality control process in manufacturing it is often necess...
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06/26/2019
Selective Inference via Marginal Screening for High Dimensional Classification
Post-selection inference is a statistical technique for determining sali...
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06/03/2019
Computing Valid p-values for Image Segmentation by Selective Inference
Image segmentation is one of the most fundamental tasks of computer visi...
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05/06/2019
Statistically Discriminative Sub-trajectory Mining
We study the problem of discriminative sub-trajectory mining. Given two ...
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03/08/2019
Active learning for enumerating local minima based on Gaussian process derivatives
We study active learning (AL) based on Gaussian Processes (GPs) for effi...
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01/24/2019
Multi-fidelity Bayesian Optimization with Max-value Entropy Search
Bayesian optimization (BO) is an effective tool for black-box optimizati...
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10/12/2018
Safe Grid Search with Optimal Complexity
Popular machine learning estimators involve regularization parameters th...
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10/03/2018
Learning sparse optimal rule fit by safe screening
In this paper, we consider linear prediction models in the form of a spa...
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03/01/2018
