ScholarX: LEE, JEE HYONG

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LEE, JEE HYONG (이지형)

Computing and Informatics (Computer Science and Engineering)

Research Area: Deep Learning,, Machine Learning,, Federated Learning,, Deep Learning,, Machine Learning,, Federated Learning,

Tel 031-290-7154
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Twitter:5||recommender system:3||Machine learning:3||Deep learning:3||Ridge direction:3||Deep Learning:3||deep learning:3||Data mining:3||Fingerprint classification:3||LDA:2||Convolutional Neural Network:2||Language model:2||Skidsteering:2||Image Classification:2||Convolutional Neural Networks:2||Document modeling:2||Convolutional neural network:2||Wafer Defect Map Classification:2||Navigation system:2||Rail tracking:2||Generative Adversarial Networks:2||Web Mining:2||Data Augmentation:2||Data Mining:2||Data augmentation:2||imbalanced data:2||Convolutional neural networks:2||Core block:2||Successive Halving Algorithm:2||wafer map classification:2||Support Vector Machine:2||Autonomous greenhouse sprayer:2||word embedding:2||Support vector machine:2||감성분석:2||Object detection:2||Collaborative filtering:2||SSD:2||SVM:2||TV domain:2||machine learning:2||TV program recommendation:2||Association rules:2||collaborative filtering:2||collective matrix factorization:2||Machine Learning:2||Boosted Decision Tree:2||Paragraph vector:2||natural language processing:2||Markov model:2||convolutional neural network:2||Selftraining:2||outofdistribution:2||Feature Selection:2||트위터:2||Attention mechanism:2||Semisupervised learning:2||Dimensionality reduction:2||Sentiment Analysis:2||Conditional probability:2||Monte Carlo Tree Search (MCTS):2||Turning algorithm:2||failure analysis:2||feature selection:2||Division of region:2||Directed acyclic graph:1||Document Content Memory:1||Document Management System:1||Documentmodification relation:1||Domain Shift:1||Esports video highlighting:1||EVBT:1||Energy Consumption:1||Event sequential pattern:1||Experience based testing:1||Expertbased Recommender System:1||Extraction:1||Failure analysis:1||False Negative Rejection:1||Feature Augmentation:1||Feature Extraction:1||Feature Vector:1||Feature selection:1||Federated Learning:1||Formatting:1||Fuzzy logic:1||GDSII:1||Game prediction:1||Gaussian Process Regression:1||Generative approach:1||Genetic Algorithm:1||Genetic algorithms:1||Genetic programming:1||GradCam:1||Group modeling:1||Group recommendation system:1||HMOTiFS:1||Hazardous weather:1||Health and safety:1||Heavy Rain Prediction:1||Heuristic Feature Selection:1||Heuristic feature selection:1||Heuristic function:1||Heuristic undersampling method:1||High Speed Test:1||Home group:1||Hyperparameter:1||Hyperparameter Search:1||Image Processing:1||Image recognition:1||Imbalanced Problem:1||Implementation Pattern:1||Improved Kmeans algorithm:1||InContext Learning:1||Industry:1||Information Gap:1||Information Retrieval:1||Information objects:1||Information retrieval topic extraction:1||Interaction:1||Internet article:1||Intimate Friends:1||Java Method Signature:1||Kalman filter:1||KeyWords:  classification:1||Keyphrase Extraction:1||Keyphrase extraction:1||Knowledge Fusion:1||Knowledge diagnosis:1||Knowledge visualization:1||Labeling:1||Large Language Models:1||Latent Dirichlet Allocation(LDA):1||Latent Keyphrase:1||Latent keyphrase:1||Lithography hotspot detection:1||Livescanned fingerprint:1||Location awareness:1||Location based service:1||Logical Structure Analysis:1||Logit Averaging:1||Longtail recommendation:1||MCBT:1||MMORPGs:1||MNIST classification:1||MOTiFS:1||Major Information:1||Markov models:1||Mask data conversion:1||Meaningful location:1||Model Selection:1||Monte Carlo Search:1||MultiLabel Learning:1||Multidocument summarization:1||Multilabel classification:1||Multilabel learning:1||Multiple linear regression:1||Music recommendation:1||Npair contrastive loss function:1||NLP:1||Natural language processing:1||Nearest neighbor search:1||Neighbor Document:1||Network monitoring:1||Neural Network:1||Neural networks:1||NonIID:1||OCR:1||OOV:1||Occupational health:1||Occupational safety:1||Ontology:1||Optimal control:1||Outofdistribution:1||Package Yield:1||Path prediction:1||Path simplification:1||Pattern extraction:1||Pattern recognition:1||Personal Social Network:1||Personalized Expert:1||Personalized experts:1||Photomask:1||Pointer mechanism:1||Postfiltering:1||Prediction method:1||Predictive models:1||Probe Test:1||Probing Pad Defects:1||Prompting:1||Query classification:1||RMOTiFS:1||RandomForest:1||Recommender System:1||Recommender system:1||Recurrent Neural Networks:1||Recurrent Neural Networks EncoderDecoder:1||Regional prediction:1||Reinforcement learning:1||Rejection Rule:1||Relative average distance:1||Result clustering:1||SVM ensemble method:1||Scanning electron microscopy:1||Scarce Labeled Samples:1||Selective Update:1||Self&:1||SelfTraining technique:1||Selfguided Exploitation:1||Semantic Web:1||Semisupervised Learning:1||Semiconductor:1||Semiconductor manufacturing:1||Sentiment analysis:1||Sequential Recommendation:1||Sequential log:1||Sessionbased recommendation:1||Shortest path problem:1||Similarity Measurement:1||Single Positive MultiLabel Learning:1||Slidingmode control:1||Slow port scan:1||Smart City:1||Smart nodes:1||Smart space:1||Social Network Service:1||Source code summarization:1||Source coding:1||Statistical Chracteristic:1||Stepwise Policy:1||Stereo Depth Estimation:1||Storytelling:1||Stream data:1||Support Vector Machine (SVM):1||Syntactics:1||Synthetic Minority Oversampling Technique:1||Synthetic document vector:1||TFIDF:1||TV Program:1||TV 프로그램:1||Task analysis:1||Term frequency smoothing:1||Test Case:1||TestTime Adaptation:1||Text Mining:1||Text classification:1||Text mining:1||Text operation:1||TextRank:1||Timeweighted clustering:1||Topic trend change:1||TransUNet:1||Transfer Learning:1||Transformers:1||Trimming die design:1||UINModel:1||Ultraprecision position:1||User Modeling:1||User Preference:1||User behavior analysis:1||Video summarization:1||Viewing time Patterns:1||Virtual Backbone Tree:1||VisionLanguage Model:1||WSN:1||Wafer map:1||Wafer map classification:1||Wafer productivity:1||Web context:1||Web page ranking:1||Weighted cost function:1||Winloss probability:1||Word embedding:1||XGBoost:1||Yield Prediction:1||Yield modeling:1||abstract syntax tree:1||abstractive summarization:1||adaptive transformer:1||adversarial loss:1||adverse drug reaction:1||association rule mining:1||attention mechanism:1||auxiliary discriminator:1||bot detection model:1||characterlevel CNN:1||code defect detection:1||content preservation:1||contentbased filtering:1||context awareness:1||contextaware:1||contextual similiarity:1||convolutionalneural network:1||data augmentation:1||data membership:1||deep reinforcement learning:1||dimensionality reduction:1||disproportionality analysis:1||docetaxel:1||document content memory:1||document summarization:1||emotion recognition:1||entailment relation inference:1||example forgetting event:1||federated learning:1||filterwrapper:1||fusion network:1||game play styles:1||gen:1||generative approach:1||global relation:1||group modeling:1||group recommendation system:1||heuristic feature selection:1||home group user:1||hybrid:1||hybrid flowshop problem:1||identity loss:1||image classification:1||image quality assessment:1||image transfer:1||incongruity attention:1||information density:1||information retrieval:1||kmeans clustering:1||keyphrase generation:1||keyword extraction:1||language model:1||latent vector:1||linelevel defect localization:1||lithography hotspot detection:1||location based service:1||longtail distribution:1||lossy compression:1||machine learning algorithms:1||manufacturing intelligence:1||matrix factorization:1||memory networks:1||meta &:1||mixedtype wafer maps:1||monte Carlo tree search (MCTS):1||multicontent disentanglement:1||multitask learning:1||neighbor document:1||nivolumab:1||object detection:1||outofvocabulary (OOV):1||path selection:1||primitive word combination:1||quadratic programming:1||quantized shallow Siamese convolutional neural networks:1||recommender systems:1||recurrent neural network:1||s location prediction:1||sarcasm detection:1||scheduling:1||semi&:1||semisupervised learning:1||semiconductor:1||sentiment transfer:1||sequence to sequence:1||sessionbased recommendation:1||shortest path:1||signal detection:1||smart factory:1||source code summarization:1||sparsity problem:1||subtopic model:1||tag:1||tag information:1||temporal context:1||text classification:1||text mining:1||text modification:1||time aware recommendation:1||time context:1||timeaware recommendation:1||transformer:1||transformer layer:1||unified multitask training:1||unsupervised learning:1||user&apos:1||web page recommendation:1||weighted averaging:1||wrapper:1||경험 기반 테스팅:1||고객 이탈 예측:1||데이터 마이닝:1||딥 러닝:1||문서 요약:1||반감독 학습 기법:1||불량 검출:1||블랙박스 테스팅:1||수반 관계 추론:1||순환 신경망:1||시청시간패턴:1||신경망:1||유사도 측정:1||이웃 문서:1||자연어 처리:1||잠재 디리클레 할당(LDA):1||잠재 키워드:1||초매개변수 탐색:1||추천 시스템:1||키워드 추출:1||테스트 케이스:1||텍스트 랭크:1||통계적 특징:1||행동 패턴:1||Abnormal traffic control framework:1||협업 필터링:1||Abstractive summarization:1||Abstractive text summarization:1||Accumulationbased attention:1||Activity recognition:1||Actorcritic algorithm:1||Adaptive behavior:1||Adaptive systems:1||Adversarial Attack:1||Adversarial Defense:1||Adversarial Detection:1||Adversarial Training:1||Algorithms:1||Attack detection:1||Attribute selection:1||Auto defect classification:1||Auto design inspection:1||Automation:1||Autonomic level:1||Autonomic machine learning platform:1||Bayesian Optimization:1||Bayesian network:1||Behavior Pattern:1||Behavioral data:1||Big Data Mining:1||Big data:1||Biometrics:1||Black box testing:1||Blog text mining:1||Blogs:1||CNN:1||Cascade KMedoids:1||Catastrophic Forgetting:1||Chronological cohesive unit:1||Classification:1||Classification algorithm:1||Codes:1||Collaborative Filtering:1||Collaborative Filtering (CF):1||Collaborative filter:1||Communication network data:1||Computational cost:1||Conditional entropy:1||Confirmation Bias:1||Contentbased recommendation:1||Context aware:1||Context compensation:1||Continuous action space:1||Contrastive Learning:1||Core content:1||Cost Effective:1||CostSensitive Support Vector Machine (CSVM):1||Costsensitive Support Vector Machin:1||Costs:1||Customer Churn Prediction:1||Customer Churn Predictive Model:1||CycleGAN:1||DNA data storage:1||Data distribution:1||Data models:1||Data structures:1||Debiasing:1||Deep Sparse Neural Network:1||Deep belief networks:1||Defect detection:1||

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(03063) 25-2, SUNGKYUNKWAN-RO, JONGNO-GU, SEOUL, KOREA samsunglib@skku.edu

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