Ikko Yamane

According to our database, Ikko Yamane authored at least 11 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Scalable and hyper-parameter-free non-parametric covariate shift adaptation with conditional sampling.

François Portier, Lionel Truquet, Ikko Yamane

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.

Takashi Ishida, Ikko Yamane, Nontawat Charoenphakdee, Gang Niu, Masashi Sugiyama

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality.

Ikko Yamane, Yann Chevaleyre, Takashi Ishida, Florian Yger

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2021

A One-Step Approach to Covariate Shift Adaptation.

Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama

SN Comput. Sci., 2021

Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences.

Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 2021

Skew-symmetrically perturbed gradient flow for convex optimization.

Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Do We Need Zero Training Loss After Achieving Zero Training Error?

Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

Uplift Modeling from Separate Labels.

Ikko Yamane, Florian Yger, Jamal Atif, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation.

Ikko Yamane, Hiroaki Sasaki, Masashi Sugiyama

Neural Comput., 2016

Multitask Principal Component Analysis.

Ikko Yamane, Florian Yger, Maxime Berar, Masashi Sugiyama

Proceedings of The 8th Asian Conference on Machine Learning, 2016

2015

A Fourier-Analytic Approach to List-Decoding for Sparse Random Linear Codes.

Akinori Kawachi, Ikko Yamane

IEICE Trans. Inf. Syst., 2015