3 citations · 9 across the 16 of their papers we have counts for
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cs.IR2022★ 2 cited
Debiasing Graph Transfer Learning via Item Semantic Clustering for Cross-Domain Recommendations
Zhi Li, Daichi Amagata, Yihong Zhang +4
Deep learning-based recommender systems may lead to over-fitting when lacking training interaction data. This over-fitting significantly degrades recommendation performances. To ad…
cs.DB2022
Learned k-NN Distance Estimation
Daichi Amagata, Yusuke Arai, Sumio Fujita +1
Big data mining is well known to be an important task for data science, because it can provide useful observations and new knowledge hidden in given large datasets. Proximity-based…
cs.DB2022★ 2 cited
Fast Density-Peaks Clustering: Multicore-based Parallelization Approach
Daichi Amagata, Takahiro Hara
Clustering multi-dimensional points is a fundamental task in many fields, and density-based clustering supports many applications as it can discover clusters of arbitrary shapes. T…