Nontawat Charoenphakdee

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 34

Top Topics

Empirical Risk Minimization

Imitation Learning

Multiclass Classification

Top Venues

Publications

Kenta Oono, Nontawat Charoenphakdee, Kotatsu Bito, Zhengyan Gao, Yoshiaki Ota, Shoichiro Yamaguchi, Yohei Sugawara, Shin-ichi Maeda, Kunihiko Miyoshi, Yuki Saito, Koki Tsuda, Hiroshi Maruyama, Kohei Hayashi
Virtual Human Generative Model: Masked Modeling Approach for Learning Human Characteristics. CoRR (2023)
Takashi Ishida, Ikko Yamane, Nontawat Charoenphakdee, Gang Niu, Masashi Sugiyama
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification. ICLR (2023)
Takashi Ishida, Ikko Yamane, Nontawat Charoenphakdee, Gang Niu, Masashi Sugiyama
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification. CoRR (2022)
Shuhan Zheng, Nontawat Charoenphakdee
Diffusion models for missing value imputation in tabular data. CoRR (2022)
Nuttapong Chairatanakul, Noppayut Sriwatanasakdi, Nontawat Charoenphakdee, Xin Liu, Tsuyoshi Murata
Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph. EMNLP (Findings) (2021)
Voot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama
Robust Imitation Learning from Noisy Demonstrations. AISTATS (2021)
Nuttapong Chairatanakul, Noppayut Sriwatanasakdi, Nontawat Charoenphakdee, Xin Liu, Tsuyoshi Murata
Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph. CoRR (2021)
Nontawat Charoenphakdee, Jayakorn Vongkulbhisal, Nuttapong Chairatanakul, Masashi Sugiyama
On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective. CVPR (2021)
Nontawat Charoenphakdee, Jongyeong Lee, Masashi Sugiyama
A Symmetric Loss Perspective of Reliable Machine Learning. CoRR (2021)
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
Classification with Rejection Based on Cost-sensitive Classification. ICML (2021)
Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
Semisupervised Ordinal Regression Based on Empirical Risk Minimization. Neural Comput. 33 (12) (2021)
Yivan Zhang, Nontawat Charoenphakdee, Zhenguo Wu, Masashi Sugiyama
Learning from Aggregate Observations. NeurIPS (2020)
Zhenghang Cui, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
Classification from Triplet Comparison Data. Neural Comput. 32 (3) (2020)
Nontawat Charoenphakdee, Jayakorn Vongkulbhisal, Nuttapong Chairatanakul, Masashi Sugiyama
On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective. CoRR (2020)
Hideaki Imamura, Nontawat Charoenphakdee, Futoshi Futami, Issei Sato, Junya Honda, Masashi Sugiyama
Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time. CoRR (2020)
Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang, Masashi Sugiyama
Classification with Rejection Based on Cost-sensitive Classification. CoRR (2020)
Yivan Zhang, Nontawat Charoenphakdee, Zhenguo Wu, Masashi Sugiyama
Learning from Aggregate Observations. CoRR (2020)
Voot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama
Robust Imitation Learning from Noisy Demonstrations. CoRR (2020)
Nontawat Charoenphakdee, Jongyeong Lee, Yiping Jin, Dittaya Wanvarie, Masashi Sugiyama
Learning Only from Relevant Keywords and Unlabeled Documents. CoRR (2019)
Chenri Ni, Nontawat Charoenphakdee, Junya Honda, Masashi Sugiyama
On Possibility and Impossibility of Multiclass Classification with Rejection. CoRR (2019)
Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama
Unsupervised Domain Adaptation Based on Source-Guided Discrepancy. AAAI (2019)
Nontawat Charoenphakdee, Jongyeong Lee, Masashi Sugiyama
On Symmetric Losses for Learning from Corrupted Labels. CoRR (2019)
Yueh-Hua Wu, Nontawat Charoenphakdee, Han Bao, Voot Tangkaratt, Masashi Sugiyama
Imitation Learning from Imperfect Demonstration. CoRR (2019)
Yivan Zhang, Nontawat Charoenphakdee, Masashi Sugiyama
Learning from Indirect Observations. CoRR (2019)
Nontawat Charoenphakdee, Masashi Sugiyama
Positive-Unlabeled Classification under Class Prior Shift and Asymmetric Error. SDM (2019)
Zhenghang Cui, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
Classification from Triplet Comparison Data. CoRR (2019)
Jongyeong Lee, Nontawat Charoenphakdee, Seiichi Kuroki, Masashi Sugiyama
Domain Discrepancy Measure Using Complex Models in Unsupervised Domain Adaptation. CoRR (2019)
Nontawat Charoenphakdee, Jongyeong Lee, Yiping Jin, Dittaya Wanvarie, Masashi Sugiyama
Learning Only from Relevant Keywords and Unlabeled Documents. EMNLP/IJCNLP (1) (2019)
Chenri Ni, Nontawat Charoenphakdee, Junya Honda, Masashi Sugiyama
On the Calibration of Multiclass Classification with Rejection. NeurIPS (2019)
Yueh-Hua Wu, Nontawat Charoenphakdee, Han Bao, Voot Tangkaratt, Masashi Sugiyama
Imitation Learning from Imperfect Demonstration. ICML (2019)
Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama
Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization. CoRR (2019)
Nontawat Charoenphakdee, Jongyeong Lee, Masashi Sugiyama
On Symmetric Losses for Learning from Corrupted Labels. ICML (2019)
Nontawat Charoenphakdee, Masashi Sugiyama
Positive-Unlabeled Classification under Class Prior Shift and Asymmetric Error. CoRR (2018)
Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao, Junya Honda, Issei Sato, Masashi Sugiyama
Unsupervised Domain Adaptation Based on Source-guided Discrepancy. CoRR (2018)