6 citations · 11 across the 4 of their papers we have counts for
4 papers
TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering
Seoyoung Hong, Minju Jo, Seungji Kook +4
Recommender systems are a long-standing research problem in data mining and machine learning. They are incremental in nature, as new user-item interaction logs arrive. In real-worl…
LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations
Jaehoon Lee, Jinsung Jeon, Sheo yon Jhin +5
The problem of processing very long time-series data (e.g., a length of more than 10,000) is a long-standing research problem in machine learning. Recently, one breakthrough, calle…
LightMove: A Lightweight Next-POI Recommendation for Taxicab Rooftop Advertising
Jinsung Jeon, Soyoung Kang, Minju Jo +4
Mobile digital billboards are an effective way to augment brand-awareness. Among various such mobile billboards, taxicab rooftop devices are emerging in the market as a brand new m…
ACE-NODE: Attentive Co-Evolving Neural Ordinary Differential Equations
Sheo Yon Jhin, Minju Jo, Taeyong Kong +2
Neural ordinary differential equations (NODEs) presented a new paradigm to construct (continuous-time) neural networks. While showing several good characteristics in terms of the n…