70 citations · 245 across the 36 of their papers we have counts for
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stat.ML2018
Dueling Bandits with Qualitative Feedback
Liyuan Xu, Junya Honda, Masashi Sugiyama
We formulate and study a novel multi-armed bandit problem called the qualitative dueling bandit (QDB) problem, where an agent observes not numeric but qualitative feedback by pulli…
cs.LG2018★ 7 cited
Unsupervised Domain Adaptation Based on Source-guided Discrepancy
Seiichi Kuroki, Nontawat Charoenphakdee, Han Bao +3
Unsupervised domain adaptation is the problem setting where data generating distributions in the source and target domains are different, and labels in the target domain are unavai…