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Issue Date	Title / Author(s) / Citation	File
2008	Computerized classifier using quantitative analysis and medical images : application to the lung 김남국	link
2009	Multiple Context-based Relation Kernel Models for Text Mining 엄재홍	link
2011	Machine Learning Approach to select appropriate target compute devices in heterogeneous parallel computing Dao Thanh Tuan	link
2014	A Machine Learning-based Methodology to Detect I/O Performance Bottlenecks for Hadoop Systems 성민영	view file
2014	Synthesizing and Editing Human Motion from Sparse User Inputs 김종민	view file
2015	Machine Learning Models and Missing Data Imputation Methods in Predicting the Progression of IgA Nephropathy 노준혁	view file
2015	Heterogeneous Ensemble Learning for Multi-class Classification 강석호	view file
2017	Markerless Reconstruction of Human Motion Data 양경용	view file
2017	Semantic Analysis for Human Motion Synthesis 현경렬	view file
2017	Context-based Control Strategies for Improving Energy Efficiency in Multi-zone Buildings 송권식	view file
2018	DEEP LEARNING ON GRAPHS 이재구	view file
2018	Application of Recurrent Neural Network to Prediction of Structural Deterioration 최수빈	view file
2018	Development of Survival Prediction Model for the Korean Disease-free Lung Cancer Survivors using Patient Reported Outcome variables: application to Cox proportional hazard regression model and diverse machine learning algorithms Jin-ah Sim	view file
2019	Enhancing VAEs for Collaborative Filtering: Flexible Priors & Gating Mechanisms 김대룡	view file link
2019	Interactive Control of Unorganized Human Motion using Deep Neural Networks 이경호	view file link
2019	Drowsiness Detection Based on Unconstrained Measurement of Biosignals 홍승혁	view file link
2020	Design of a Wearable-based Automated Monitoring and Reporting system in School Violence Scenarios Thanh Dung Ho	view file link
2020	머신러닝 기반의 온라인 미디어 감성분석을 통한 자동차 제조사 주가 해석에 관한 연구 박민수	view file link
2020	기계학습을 이용한 Aspect-Based Sentiment Analysis 기반 전기차 요소별 사용자 감성 분석 및 예측 모델링 정세준	view file link
2020	기계학습 방법을 이용한 급성호흡곤란증후군 환자의 예후 예측 모델 개발 김승빈	view file link

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