Satoshi Hara

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 31

Top Topics

Feature Selection

Support Vectors

Decision Tree Learning

Top Venues

Publications

Hirofumi Suzuki, Hiroaki Iwashita, Takuya Takagi, Yuta Fujishige, Satoshi Hara
Rule Mining for Correcting Classification Models. CoRR (2023)
Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara, Mario Marchand, Foutse Khomh
Fooling SHAP with Stealthily Biased Sampling. ICLR (2023)
Hirofumi Suzuki, Hiroaki Iwashita, Takuya Takagi, Yuta Fujishige, Satoshi Hara
Rule Mining for Correcting Classification Models. ICDM (2023)
Satoshi Hara, Yuichi Yoshida
Average Sensitivity of Decision Tree Learning. ICLR (2023)
Naoyuki Terashita, Satoshi Hara
Personalized Decentralized Bilevel Optimization over Stochastic and Directed Networks. CoRR (2022)
Hirofumi Suzuki, Hiroaki Iwashita, Takuya Takagi, Keisuke Goto, Yuta Fujishige, Satoshi Hara
Explainable and Local Correction of Classification Models Using Decision Trees. AAAI (2022)
Gabriel Laberge, Ulrich Aïvodji, Satoshi Hara
Fooling SHAP with Stealthily Biased Sampling. CoRR (2022)
Ulrich Aïvodji, Hiromi Arai, Sébastien Gambs, Satoshi Hara
Characterizing the risk of fairwashing. CoRR (2021)
Kazuaki Hanawa, Sho Yokoi, Satoshi Hara, Kentaro Inui
Evaluation of Similarity-based Explanations. ICLR (2021)
Ulrich Aïvodji, Hiromi Arai, Sébastien Gambs, Satoshi Hara
Characterizing the risk of fairwashing. NeurIPS (2021)
Kazuto Fukuchi, Satoshi Hara, Takanori Maehara
Faking Fairness via Stealthily Biased Sampling. AAAI (2020)
Danqing Pan, Tong Wang, Satoshi Hara
Interpretable Companions for Black-Box Models. AISTATS (2020)
Danqing Pan, Tong Wang, Satoshi Hara
Interpretable Companions for Black-Box Models. CoRR (2020)
Kazuaki Hanawa, Sho Yokoi, Satoshi Hara, Kentaro Inui
Evaluation Criteria for Instance-based Explanation. CoRR (2020)
Ulrich Aïvodji, Hiromi Arai, Olivier Fortineau, Sébastien Gambs, Satoshi Hara, Alain Tapp
Fairwashing: the risk of rationalization. ICML (2019)
Kazuto Fukuchi, Satoshi Hara, Takanori Maehara
Pretending Fair Decisions via Stealthily Biased Sampling. CoRR (2019)
Satoshi Hara, Atsushi Nitanda, Takanori Maehara
Data Cleansing for Models Trained with SGD. CoRR (2019)
Ulrich Aïvodji, Hiromi Arai, Olivier Fortineau, Sébastien Gambs, Satoshi Hara, Alain Tapp
Fairwashing: the risk of rationalization. CoRR (2019)
Satoshi Hara, Atsushi Nitanda, Takanori Maehara
Data Cleansing for Models Trained with SGD. NeurIPS (2019)
Satoshi Hara, Takanori Maehara
Convex Hull Approximation of Nearly Optimal Lasso Solutions. PRICAI (2) (2019)
Satoshi Hara, Weichih Chen, Takashi Washio, Tetsuichi Wazawa, Takeharu Nagai
SPoD-Net: Fast Recovery of Microscopic Images Using Learned ISTA. ACML (2019)
Kentaro Kanamori, Satoshi Hara, Masakazu Ishihata, Hiroki Arimura
Enumeration of Distinct Support Vectors for Interactive Decision Making. CoRR (2019)
Satoshi Hara, Kouichi Ikeno, Tasuku Soma, Takanori Maehara
Maximally Invariant Data Perturbation as Explanation. CoRR (2018)
Satoshi Hara, Masakazu Ishihata
Approximate and Exact Enumeration of Rule Models. AAAI (2018)
Hiroki Yanagisawa, Satoshi Hara
Discounted average degree density metric and new algorithms for the densest subgraph problem. Networks 71 (1) (2018)
Satoshi Hara, Kohei Hayashi
Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach. AISTATS (2018)
Satoshi Hara, Takanori Maehara
Convex Hull Approximation of Nearly Optimal Lasso Solutions. CoRR (2018)
Kouichi Ikeno, Satoshi Hara
Maximizing Invariant Data Perturbation with Stochastic Optimization. CoRR (2018)
Satoshi Hara, Takayuki Katsuki, Hiroki Yanagisawa, Takafumi Ono, Ryo Okamoto, Shigeki Takeuchi
Consistent and Efficient Nonparametric Different-Feature Selection. AISTATS (2017)
Satoshi Hara, Takanori Maehara
Enumerate Lasso Solutions for Feature Selection. AAAI (2017)
Satoshi Hara, Tetsuro Morimura, Toshihiro Takahashi, Hiroki Yanagisawa, Taiji Suzuki
A Consistent Method for Graph Based Anomaly Localization. AISTATS (2015)
Satoshi Hara, Rudy Raymond, Tetsuro Morimura, Hidemasa Muta
Predicting halfway through simulation: early scenario evaluation using intermediate features of agent-based simulations. WSC (2014)
Hidemasa Muta, Rudy Raymond, Satoshi Hara, Tetsuro Morimura
A multi-objective genetic algorithm using intermediate features of simulations. WSC (2014)
Satoshi Hara, Takashi Washio
Learning a common substructure of multiple graphical Gaussian models. Neural Networks 38 (2013)
Satoshi Hara, Takashi Washio
Anomalous Neighborhood Selection. ICDM Workshops (2012)
Satoshi Hara, Yoshinobu Kawahara, Takashi Washio, Paul von Bünau, Terumasa Tokunaga, Kiyohumi Yumoto
Separation of stationary and non-stationary sources with a generalized eigenvalue problem. Neural Networks 33 (2012)
Satoshi Hara, Takashi Washio
Group Sparse Inverse Covariance Selection with a Dual Augmented Lagrangian Method. ICONIP (3) (2012)
Satoshi Hara, Takashi Washio
Common Substructure Learning of Multiple Graphical Gaussian Models. ECML/PKDD (2) (2011)
Masashi Sugiyama, Satoshi Hara, Paul von Bünau, Taiji Suzuki, Takafumi Kanamori, Motoaki Kawanabe
Direct Density Ratio Estimation with Dimensionality Reduction. SDM (2010)
Satoshi Hara, Yoshinobu Kawahara, Takashi Washio, Paul von Bünau
Stationary Subspace Analysis as a Generalized Eigenvalue Problem. ICONIP (1) (2010)