activity
20182021
most citedImitation Learning from Imperfect Demonstration

16 citations · 24 across the 5 of their papers we have counts for

collaborators

15 papers

cs.CL2021

Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph

Nuttapong Chairatanakul, Noppayut Sriwatanasakdi, Nontawat Charoenphakdee +2

In cross-lingual text classification, it is required that task-specific training data in high-resource source languages are available, where the task is identical to that of a low-…

stat.ML20202 cited

On Focal Loss for Class-Posterior Probability Estimation: A Theoretical Perspective

Nontawat Charoenphakdee, Jayakorn Vongkulbhisal, Nuttapong Chairatanakul +1

The focal loss has demonstrated its effectiveness in many real-world applications such as object detection and image classification, but its theoretical understanding has been limi…

stat.ML2020

Classification with Rejection Based on Cost-sensitive Classification

Nontawat Charoenphakdee, Zhenghang Cui, Yivan Zhang +1

The goal of classification with rejection is to avoid risky misclassification in error-critical applications such as medical diagnosis and product inspection. In this paper, based…

stat.ML2020

Robust Imitation Learning from Noisy Demonstrations

Voot Tangkaratt, Nontawat Charoenphakdee, Masashi Sugiyama

Robust learning from noisy demonstrations is a practical but highly challenging problem in imitation learning. In this paper, we first theoretically show that robust imitation lear…

stat.ML2020

Learning from Aggregate Observations

Yivan Zhang, Nontawat Charoenphakdee, Zhenguo Wu +1

We study the problem of learning from aggregate observations where supervision signals are given to sets of instances instead of individual instances, while the goal is still to pr…

stat.ML2020

Time-varying Gaussian Process Bandit Optimization with Non-constant Evaluation Time

Hideaki Imamura, Nontawat Charoenphakdee, Futoshi Futami +3

The Gaussian process bandit is a problem in which we want to find a maximizer of a black-box function with the minimum number of function evaluations. If the black-box function var…