297 citations · 338 across the 4 of their papers we have counts for
5 papers
SR-GCL: Session-Based Recommendation with Global Context Enhanced Augmentation in Contrastive Learning
Eunkyu Oh, Taehun Kim, Minsoo Kim +2
Session-based recommendations aim to predict the next behavior of users based on ongoing sessions. The previous works have been modeling the session as a variable-length of a seque…
STING: Self-attention based Time-series Imputation Networks using GAN
Eunkyu Oh, Taehun Kim, Yunhu Ji +1
Time series data are ubiquitous in real-world applications. However, one of the most common problems is that the time series data could have missing values by the inherent nature o…
UACANet: Uncertainty Augmented Context Attention for Polyp Segmentation
Taehun Kim, Hyemin Lee, Daijin Kim
We propose Uncertainty Augmented Context Attention network (UACANet) for polyp segmentation which consider a uncertain area of the saliency map. We construct a modified version of…
Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations
Ranggi Hwang, Taehun Kim, Youngeun Kwon +1
Personalized recommendations are the backbone machine learning (ML) algorithm that powers several important application domains (e.g., ads, e-commerce, etc) serviced from cloud dat…
Fast and Accurate Transferability Measurement for Heterogeneous Multivariate Data
Seungcheol Park, Huiwen Xu, Taehun Kim +3
Given a set of heterogeneous source datasets with their classifiers, how can we quickly find the most useful source dataset for a specific target task? We address the problem of me…