Picture for Ken Kobayashi

Ken Kobayashi

Learning Decision Trees and Forests with Algorithmic Recourse

Add code
Jun 03, 2024
Figure 1 for Learning Decision Trees and Forests with Algorithmic Recourse
Figure 2 for Learning Decision Trees and Forests with Algorithmic Recourse
Figure 3 for Learning Decision Trees and Forests with Algorithmic Recourse
Figure 4 for Learning Decision Trees and Forests with Algorithmic Recourse
Viaarxiv icon

SCOPE-RL: A Python Library for Offline Reinforcement Learning and Off-Policy Evaluation

Add code
Dec 04, 2023
Viaarxiv icon

Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation

Add code
Dec 04, 2023
Figure 1 for Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
Figure 2 for Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
Figure 3 for Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
Figure 4 for Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
Viaarxiv icon

An IPW-based Unbiased Ranking Metric in Two-sided Markets

Add code
Jul 14, 2023
Figure 1 for An IPW-based Unbiased Ranking Metric in Two-sided Markets
Figure 2 for An IPW-based Unbiased Ranking Metric in Two-sided Markets
Figure 3 for An IPW-based Unbiased Ranking Metric in Two-sided Markets
Figure 4 for An IPW-based Unbiased Ranking Metric in Two-sided Markets
Viaarxiv icon

Counterfactual Explanation with Missing Values

Add code
Apr 28, 2023
Viaarxiv icon

Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization

Add code
May 23, 2022
Figure 1 for Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization
Figure 2 for Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization
Figure 3 for Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization
Figure 4 for Bézier Flow: a Surface-wise Gradient Descent Method for Multi-objective Optimization
Viaarxiv icon

A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization

Add code
Mar 29, 2022
Figure 1 for A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization
Figure 2 for A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization
Figure 3 for A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization
Figure 4 for A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization
Viaarxiv icon

Approximate Bayesian Computation of Bézier Simplices

Add code
Apr 13, 2021
Figure 1 for Approximate Bayesian Computation of Bézier Simplices
Figure 2 for Approximate Bayesian Computation of Bézier Simplices
Figure 3 for Approximate Bayesian Computation of Bézier Simplices
Figure 4 for Approximate Bayesian Computation of Bézier Simplices
Viaarxiv icon

Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization

Add code
Dec 22, 2020
Figure 1 for Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization
Figure 2 for Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization
Figure 3 for Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization
Figure 4 for Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization
Viaarxiv icon

Prediction of hierarchical time series using structured regularization and its application to artificial neural networks

Add code
Jul 30, 2020
Figure 1 for Prediction of hierarchical time series using structured regularization and its application to artificial neural networks
Figure 2 for Prediction of hierarchical time series using structured regularization and its application to artificial neural networks
Figure 3 for Prediction of hierarchical time series using structured regularization and its application to artificial neural networks
Figure 4 for Prediction of hierarchical time series using structured regularization and its application to artificial neural networks
Viaarxiv icon