Publications


Peer-Reviewed Papers

Learning Fair Representation via Distributional Contrastive Disentanglement

Changdae Oh, Heeji Won, Junhyuk So, Taero Kim, Yewon Kim, Hosik Choi, Kyungwoo Song

KDD 2022

[paper]


From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model

HeeSun BAE, Seungjae Shin, JoonHo Jang, Byeonghu Na, Kyungwoo Song, Il-Chul Moon

ICML 2022

[paper]


Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation

Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-chul Moon

ICML 2022

[paper]


Approximate Inference for Spectral Mixture Kernel
Yohan Jung, Kyungwoo Song, Jinkyoo Park

ICML 2022
[
paper]


LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning
Yooon-Yeong Kim, Kyungwoo Song, JoonHo Jang, Il-chul Moon

NeurIPS 2021
[
paper]


Implicit Kernel Attention

Kyungwoo Song, Yohan Jung, Dongjun Kim, Il-Chul Moon

AAAI 2021

[paper] [code]


Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder

Hyemi Kim, Seungjae Shin, JoonHo Jang, Kyungwoo Song, Weonyoung Joo, Wanmo Kang, Il-Chul Moon.

AAAI 2021

[paper]


Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation

Seungjae Shin, Kyungwoo Song, JoonHo Jang, Hyemi Kim, Weonyoung Joo, Il-Chul Moon

Findings of EMNLP 2020

[paper]


Deep Generative Positive-Unlabeled Learning under Selection Bias

ByeongHu Na, Hyemi Kim, Kyungwoo Song, Weonyoung Joo, Yoonyeong Kim, Il-Chul Moon

CIKM 2020

[paper]


Context Aware Sequence Modeling

Kyungwoo Song

IJCAI 2020 Doctoral Consortium

[paper]


Bivariate Beta-LSTM
Kyungwoo Song, JoonHo Jang, Seungjae Shin, Il-Chul Moon
AAAI 2020
[
paper] [code]


Hierarchically Clustered Representation Learning
Su-Jin Shin, Kyungwoo Song, Il-Chul Moon
AAAI 2020
[
paper]


Sequential Recommendation with Relation-Aware Kernelized Self-Attention
Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoonyeong Kim, Il-Chul Moon
AAAI 2020
[
paper]


Hierarchical Context enabled Recurrent Neural Network for Recommendation
Kyungwoo Song*, Mingi Ji*, Sungrae Park, Il-Chul Moon
AAAI 2019
[
paper] [code]


Adversarial Dropout for Recurrent Neural Networks
Sungrae Park, Kyungwoo Song, Mingi Ji, Wonsung Lee, Il-Chul Moon
AAAI 2019
[
paper] [code]


Ballistic Coefficient Estimation with Gaussian Process Particle Filter
Il-Chul Moon, Jinhyung Tak, Sang-Hyeon Kim, Kyungwoo Song
ICCAS 2018
[
paper]


Neural Ideal Point Estimation Network
Kyungwoo Song, Wonsung Lee, Il-Chul Moon
AAAI 2018
[
paper] [code]


State Prediction of High-speed Ballistic Vehicles with Gaussian Process
Il-Chul Moon, Kyungwoo Song, Sang-Hyeon Kim, Han-Lim Choi
IJCAS 2018
[
paper]


Augmented Variational Autoencoders for Collaborative Filtering with Auxiliary Information
Wonsung Lee, Kyungwoo Song, Il-Chul Moon
CIKM 2017
[
paper]


Data-driven ballistic coefficient learning for future state prediction of high-speed vehicles
Kyungwoo Song, Sang-Hyeon Kim, Jinhyung Tak, Han-Lim Choi, Il-Chul Moon
FUSION 2016
[
paper] [slide]


Identifying the evolution of disasters and responses with network-text analysis
Kyungwoo Song, Do-Hyeong Kim, Su-Jin Shin, Il-Chul Moon
SMC 2014
[
paper] [slide]

Under Review

COVID-19 Infection Inference with Graph Neural Networks

Kyungwoo Song, Hojun Park, Junggu Lee, Arim Kim, Jaehun Jung


Multi-Modal Mixup for Robust Fine-tuning

Junhyuk So, Changdae Oh, Minchul Shin, Kyungwoo Song

[paper]


Dirichlet Stochastic Weights Averaging for Graph Neural Networks

Minhoi Park, Kyungwoo Song


D2CL: Dataset Distillation for Continual Learning

DongHyeok Shin, JoonHo Jang, Byeonghu Na, Kyungwoo Song, Il-Chul Moon


Ordered Risk and Confidence Regularization for Robust Training from Biased Dataset

Seungjae Shin, Byeonghu Na, HeeSun Bae, JoonHo Jang, Hyemi Kim, Kyungwoo Song, Youngjae Cho, Il-chul Moon


Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation

JoonHo Jang, Byeonghu Na, DongHyeok Shin, Mingi Ji, Kyungwoo Song, Il-Chul Moon


Posterior-Aided Regularization for Likelihood-Free Inference
Dongjun Kim, Kyungwoo Song, Seungjae Shin, Wanmo Kang, Il-Chul Moon
[
paper]


Sequential Likelihood-Free Inference with Implicit Surrogate Proposal
Dongjun Kim, Kyungwoo Song, Yoonyeong Kim, Yongjin Shin, Il-Chul Moon
[
paper]


Adversarial Likelihood-Free Inference on Black-Box Generator
Dongjun Kim, Weonyoung Joo, Seungjae Shin, Kyungwoo Song, Il-Chul Moon
[
paper]

Tutorial

Shortcut learning in Machine Learning: Challenges, Analysis, Solutions

Sanghyuk Chun, Kyungwoo Song, Yonghan Jung

FAccT 2022 Translation/Dialogue Tutorial