28 citations · 65 across the 12 of their papers we have counts for
6 papers · 1 filter
Signed Graph Diffusion Network
Jinhong Jung, Jaemin Yoo, U Kang
Given a signed social graph, how can we learn appropriate node representations to infer the signs of missing edges? Signed social graphs have received considerable attention to mod…
T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion
Jaehun Jung, Jinhong Jung, U Kang
Temporal knowledge graphs (TKGs) inherently reflect the transient nature of real-world knowledge, as opposed to static knowledge graphs. Naturally, automatic TKG completion has dra…
Time-Aware Tensor Decomposition for Missing Entry Prediction
Dawon Ahn, Jun-Gi Jang, U Kang
Given a time-evolving tensor with missing entries, how can we effectively factorize it for precisely predicting the missing entries? Tensor factorization has been extensively utili…
Ensemble Multi-Source Domain Adaptation with Pseudolabels
Seongmin Lee, Hyunsik Jeon, U Kang
Given multiple source datasets with labels, how can we train a target model with no labeled data? Multi-source domain adaptation (MSDA) aims to train a model using multiple source…
Fast Partial Fourier Transform
Yong-chan Park, Jun-Gi Jang, U Kang
Given a time series vector, how can we efficiently compute a specified part of Fourier coefficients? Fast Fourier transform (FFT) is a widely used algorithm that computes the discr…
Data Context Adaptation for Accurate Recommendation with Additional Information
Hyunsik Jeon, Bonhun Koo, U Kang
Given a sparse rating matrix and an auxiliary matrix of users or items, how can we accurately predict missing ratings considering different data contexts of entities? Many previous…