Takashi Ishida

Orcid: 0000-0003-0490-0922

Affiliations:
  • University of Tokyo, Japan


According to our database1, Takashi Ishida authored at least 12 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Learning with Complementary Labels Revisited: The Selected-Completely-at-Random Setting Is More Practical.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Learning with Complementary Labels Revisited: A Consistent Approach via Negative-Unlabeled Learning.
CoRR, 2023

Flooding Regularization for Stable Training of Generative Adversarial Networks.
CoRR, 2023

Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
LocalDrop: A Hybrid Regularization for Deep Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Learning from Noisy Complementary Labels with Robust Loss Functions.
IEICE Trans. Inf. Syst., 2022

2020
Do We Need Zero Training Loss After Achieving Zero Training Error?
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Complementary-Label Learning for Arbitrary Losses and Models.
Proceedings of the 36th International Conference on Machine Learning, 2019

2018
Binary Classification from Positive-Confidence Data.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Learning from Complementary Labels.
CoRR, 2017

Learning from Complementary Labels.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017


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