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ORCIDIkko Yamane
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2020 – today
- 2023
[c8]Ikko Yamane, Yann Chevaleyre, Takashi Ishida, Florian Yger:
Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality. AISTATS 2023: 4768-4801- [c7]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 - [i5]François Portier, Lionel Truquet, Ikko Yamane:
Scalable and hyper-parameter-free non-parametric covariate shift adaptation with conditional sampling. CoRR abs/2312.09969 (2023) - 2022
- [i4]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 abs/2202.00395 (2022) - 2021
- [j3]Tianyi Zhang
, Ikko Yamane, Nan Lu, Masashi Sugiyama:
A One-Step Approach to Covariate Shift Adaptation. SN Comput. Sci. 2(4): 319 (2021) - [c6]Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane:
Skew-symmetrically perturbed gradient flow for convex optimization. ACML 2021: 721-736 - [c5]Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama:
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. ICML 2021: 11637-11647 - [i3]Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama:
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. CoRR abs/2107.08135 (2021) - 2020
- [c4]Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama:
A One-step Approach to Covariate Shift Adaptation. ACML 2020: 65-80 - [c3]Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama:
Do We Need Zero Training Loss After Achieving Zero Training Error? ICML 2020: 4604-4614 - [i2]Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama:
Do We Need Zero Training Loss After Achieving Zero Training Error? CoRR abs/2002.08709 (2020) - [i1]Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama:
A One-step Approach to Covariate Shift Adaptation. CoRR abs/2007.04043 (2020)
2010 – 2019
- 2018
- [c2]Ikko Yamane, Florian Yger, Jamal Atif, Masashi Sugiyama:
Uplift Modeling from Separate Labels. NeurIPS 2018: 9949-9959 - 2016
- [j2]Ikko Yamane, Hiroaki Sasaki, Masashi Sugiyama:
Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation. Neural Comput. 28(7): 1388-1410 (2016) - [c1]Ikko Yamane, Florian Yger, Maxime Berar, Masashi Sugiyama:
Multitask Principal Component Analysis. ACML 2016: 302-317 - 2015
- [j1]Akinori Kawachi, Ikko Yamane:
A Fourier-Analytic Approach to List-Decoding for Sparse Random Linear Codes. IEICE Trans. Inf. Syst. 98-D(3): 532-540 (2015)
Coauthor Index
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