Ikko Yamane

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 15

Top Topics

Multitask Learning

Top Venues

Publications

François Portier, Lionel Truquet, Ikko Yamane
Scalable and hyper-parameter-free non-parametric covariate shift adaptation with conditional sampling. 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)
Ikko Yamane, Yann Chevaleyre, Takashi Ishida, Florian Yger
Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality. AISTATS (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)
Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama
A One-Step Approach to Covariate Shift Adaptation. SN Comput. Sci. 2 (4) (2021)
Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. ICML (2021)
Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. CoRR (2021)
Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Ikko Yamane
Skew-symmetrically perturbed gradient flow for convex optimization. ACML (2021)
Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama
Do We Need Zero Training Loss After Achieving Zero Training Error? CoRR (2020)
Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama
A One-step Approach to Covariate Shift Adaptation. CoRR (2020)
Takashi Ishida, Ikko Yamane, Tomoya Sakai, Gang Niu, Masashi Sugiyama
Do We Need Zero Training Loss After Achieving Zero Training Error? ICML (2020)
Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama
A One-step Approach to Covariate Shift Adaptation. ACML (2020)
Ikko Yamane, Florian Yger, Jamal Atif, Masashi Sugiyama
Uplift Modeling from Separate Labels. NeurIPS (2018)
Ikko Yamane, Florian Yger, Maxime Berar, Masashi Sugiyama
Multitask Principal Component Analysis. ACML (2016)
Ikko Yamane, Hiroaki Sasaki, Masashi Sugiyama
Regularized Multitask Learning for Multidimensional Log-Density Gradient Estimation. Neural Comput. 28 (7) (2016)
Akinori Kawachi, Ikko Yamane
A Fourier-Analytic Approach to List-Decoding for Sparse Random Linear Codes. IEICE Trans. Inf. Syst. (3) (2015)