2 citations · 3 across the 3 of their papers we have counts for
5 papers
Predictive Optimization with Zero-Shot Domain Adaptation
Tomoya Sakai, Naoto Ohsaka
Prediction in a new domain without any training sample, called zero-shot domain adaptation (ZSDA), is an important task in domain adaptation. While prediction in a new domain has g…
Regret Minimization for Causal Inference on Large Treatment Space
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi +1
Predicting which action (treatment) will lead to a better outcome is a central task in decision support systems. To build a prediction model in real situations, learning from biase…
Do We Need Zero Training Loss After Achieving Zero Training Error?
Takashi Ishida, Ikko Yamane, Tomoya Sakai +2
Overparameterized deep networks have the capacity to memorize training data with zero \emph{training error}. Even after memorization, the \emph{training loss} continues to approach…
Robust modal regression with direct log-density derivative estimation
Hiroaki Sasaki, Tomoya Sakai, Takafumi Kanamori
Modal regression is aimed at estimating the global mode (i.e., global maximum) of the conditional density function of the output variable given input variables, and has led to regr…
Binary Matrix Completion Using Unobserved Entries
Masayoshi Hayashi, Tomoya Sakai, Masashi Sugiyama
A matrix completion problem, which aims to recover a complete matrix from its partial observations, is one of the important problems in the machine learning field and has been stud…