b'Masahiro Kato'

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15 publications
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14 publications

research

∙ 07/20/2023

Synthetic Control Methods by Density Matching under Implicit Endogeneity

Synthetic control methods (SCMs) have become a crucial tool for causal i...

0 Masahiro Kato, et al. ∙

research

∙ 03/08/2023

Automatic Debiased Learning from Positive, Unlabeled, and Exposure Data

We address the issue of binary classification from positive and unlabele...

0 Masahiro Kato, et al. ∙

research

∙ 02/06/2023

Asymptotically Minimax Optimal Fixed-Budget Best Arm Identification for Expected Simple Regret Minimization

We investigate fixed-budget best arm identification (BAI) for expected s...

0 Masahiro Kato, et al. ∙

research

∙ 09/15/2022

Semiparametric Best Arm Identification with Contextual Information

We study best-arm identification with a fixed budget and contextual (cov...

2 Masahiro Kato, et al. ∙

research

∙ 03/10/2022

Spatially-Varying Bayesian Predictive Synthesis for Flexible and Interpretable Spatial Prediction

Spatial data are characterized by their spatial dependence, which is oft...

3 Danielle Cabel, et al. ∙

research

∙ 02/10/2022

Benign-Overfitting in Conditional Average Treatment Effect Prediction with Linear Regression

We study the benign overfitting theory in the prediction of the conditio...

10 Masahiro Kato, et al. ∙

research

∙ 01/31/2022

Unified Perspective on Probability Divergence via Maximum Likelihood Density Ratio Estimation: Bridging KL-Divergence and Integral Probability Metrics

This paper provides a unified perspective for the Kullback-Leibler (KL)-...

27 Masahiro Kato, et al. ∙

research

∙ 01/12/2022

Best Arm Identification with a Fixed Budget under a Small Gap

We consider the fixed-budget best arm identification problem in the mult...

17 Masahiro Kato, et al. ∙

research

∙ 11/18/2021

Optimal Simple Regret in Bayesian Best Arm Identification

We consider Bayesian best arm identification in the multi-armed bandit p...

10 Junpei Komiyama, et al. ∙

research

∙ 09/16/2021

Policy Choice and Best Arm Identification: Comments on "Adaptive Treatment Assignment in Experiments for Policy Choice"

Adaptive experimental design for efficient decision-making is an importa...

14 Kaito Ariu, et al. ∙

research

∙ 08/03/2021

Learning Causal Relationships from Conditional Moment Conditions by Importance Weighting

We consider learning causal relationships under conditional moment condi...

3 Masahiro Kato, et al. ∙

research

∙ 06/26/2021

The Role of Contextual Information in Best Arm Identification

We study the best-arm identification problem with fixed confidence when ...

0 Masahiro Kato, et al. ∙

research

∙ 05/11/2021

Scalable Personalised Item Ranking through Parametric Density Estimation

Learning from implicit feedback is challenging because of the difficult ...

0 Riku Togashi, et al. ∙

research

∙ 02/17/2021

Counterfactual Inference of the Mean Outcome under a Convergence of Average Logging Probability

Adaptive experiments, including efficient average treatment effect estim...

0 Masahiro Kato, et al. ∙

research

∙ 01/19/2021

Density-Ratio Based Personalised Ranking from Implicit Feedback

Learning from implicit user feedback is challenging as we can only obser...

0 Riku Togashi, et al. ∙

research

∙ 10/24/2020

ATRO: Adversarial Training with a Rejection Option

This paper proposes a classification framework with a rejection option t...

0 Masahiro Kato, et al. ∙

research

∙ 10/23/2020

Off-Policy Evaluation of Bandit Algorithm from Dependent Samples under Batch Update Policy

The goal of off-policy evaluation (OPE) is to evaluate a new policy usin...

7 Masahiro Kato, et al. ∙

research

∙ 10/23/2020

A Practical Guide of Off-Policy Evaluation for Bandit Problems

Off-policy evaluation (OPE) is the problem of estimating the value of a ...

13 Masahiro Kato, et al. ∙

research

∙ 10/08/2020

Theoretical and Experimental Comparison of Off-Policy Evaluation from Dependent Samples

We theoretically and experimentally compare estimators for off-policy ev...

0 Masahiro Kato, et al. ∙

research

∙ 10/03/2020

Policy Gradient with Expected Quadratic Utility Maximization: A New Mean-Variance Approach in Reinforcement Learning

In real-world decision-making problems, risk management is critical. Amo...

0 Masahiro Kato, et al. ∙

research

∙ 09/28/2020

Learning Classifiers under Delayed Feedback with a Time Window Assumption

We consider training a binary classifier under delayed feedback (DF Lear...

0 Masahiro Kato, et al. ∙

research

∙ 06/12/2020

Confidence Interval for Off-Policy Evaluation from Dependent Samples via Bandit Algorithm: Approach from Standardized Martingales

This study addresses the problem of off-policy evaluation (OPE) from dep...

0 Masahiro Kato, et al. ∙

research

∙ 06/12/2020

Non-Negative Bregman Divergence Minimization for Deep Direct Density Ratio Estimation

The estimation of the ratio of two probability densities has garnered at...

0 Masahiro Kato, et al. ∙

research

∙ 02/26/2020

Off-Policy Evaluation and Learning for External Validity under a Covariate Shift

We consider the evaluation and training of a new policy for the evaluati...

0 Masahiro Kato, et al. ∙

research

∙ 02/13/2020

Adaptive Experimental Design for Efficient Treatment Effect Estimation: Randomized Allocation via Contextual Bandit Algorithm

Many scientific experiments have an interest in the estimation of the av...

0 Masahiro Kato, et al. ∙

research

∙ 11/02/2019

Model Specification Test with Unlabeled Data: Approach from Covariate Shift

We propose a novel framework of the model specification test in regressi...

0 Masahiro Kato, et al. ∙

research

∙ 04/18/2019

Particle Filter on Episode

Differently from animals, robots can record its experience correctly for...

0 Ryuichi Ueda, et al. ∙

research

∙ 09/15/2018

Alternate Estimation of a Classifier and the Class-Prior from Positive and Unlabeled Data

We consider a problem of learning a binary classifier only from positive...

0 Masahiro Kato, et al. ∙

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