IEEE BigData

MAD: Multimodal Framework for Adaptive Time-Series Anomaly Detection

Seok, J., Han, W.

RAILL : Retrieval-Augment and Instruction Tuning for Low-resource Language Model Training

Youngjun Choi, Sungjun Lim, Minhoi Park, Jaekyeong Jung, TaeKyung Kim, Eunsik Kim, Chul-su Kim, Kyongjae Lee, Hosik Choi, Kyungwoo Song

Simple and Behavior-Driven Augmentation for Recommendation with Rich Collaborative Signals

Doyun Choi, Cheonwoo Lee, Jaemin Yoo

TSGM: Regular and Irregular Time-series Generation using Score-based Generative Models

Haksoo Lim, Jaehoon Lee, Sewon Park, Minjung Kim, and Noseong Park

Accurate Coupled Tensor Factorization with Knowledge Graph

SeungJoo Lee, Yong-chan Park, U Kang

Accurate Stock Movement Prediction via Multi-Scale and Multi-Domain Modeling

Jin-gee Kim, Yong-chan Park, Jaemin Hong, U Kang

Towards True Multi-interest Recommendation: Enhanced Scheme for Balanced Interest Training

Jaeri Lee, Jeongin Yun, U Kang

Long-term Time Series Forecasting based on Decomposition and Neural Ordinary Differential Equations

Seonkyu Lim, Jaehyeon Park, Seojin Kim, Hyowon Wi, Haksoo Lim, Jinsung Jeon, Jeongwhan Choi, and Noseong Park

Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities

Leman Akoglu, Jaemin Yoo