ScholarWorks@Korea University: KIM, Seoung Bum

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KIM, Seoung Bum (김성범)

College of Engineering (School of Industrial and Management Engineering)

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Tel 02-3290-3397
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Data mining:9||Multivariate control charts:6||Machine learning:6||Principal component analysis:5||data mining:5||Feature selection:5||Hotelling&apos:5||Clustering:4||Unsupervised learning:4||statistical process control:4||s T2:4||Feature extraction:4||deep learning:4||Bootstrap:4||Quality control:3||Timevarying process:3||Multivariate control chart:3||Statistical process control:3||Kernel density estimation:3||Classification:3||Approximate dynamic programming:2||multivariate statistical process control:2||Active learning:2||Virtual metrology:2||Ensemble:2||Uncertainty:2||Task analysis:2||Text mining:2||Process control:2||Glycol:2||Decision trees:2||Ozone pollution:2||unsupervised learning:2||Data Mining:2||Time series analysis:2||Bayesian networks:2||multivariate control chart:2||feature selection:2||text mining:2||Data mining algorithm:2||nonparametric:2||statistical quality control:2||structure learning:2||Control chart:2||Support vector data description:2||Training:2||Visualization:2||Nonlinearity:2||Clustering algorithm:2||Cuticular hydrocarbons:2||SPC:2||Multicollinearity:2||Water quality:2||Dissolved oxygen:2||False alarms:2||Novelty score:2||Average run length:2||multivariate control charts:2||Convolutional neural networks:2||Computer experiments:2||Anomaly detection:2||TFTLCD manufacturing process:2||bootstrap:2||Decomposition:2||semiconductor manufacturing:2||convolutional autoencoder:1||nonstationary time series:1||Vehicle routing:1||Stochastic gradient descent:1||Topical keyphrase extraction:1||Dispatching rule selection:1||Storage allocation:1||Class imbalance problem:1||multiagent system:1||Optimal experimental design:1||Representativeness:1||AMHS design:1||inductive learning:1||Smoothness assumption:1||Multitask learning:1||Sparse regularization:1||Academic paper recommender:1||Geodesic distance:1||Predictive model:1||Convexity:1||fault identification:1||modelbased control chart:1||Older adults:1||scheduling:1||scan statistic:1||Cross validation:1||Outofdistribution:1||Generative adversarial network:1||imbalanced class:1||convolutional neural network (CNN):1||Semantics:1||Wafer bin map defect pattern classification:1||Data models:1||Convolution:1||multichannel sensor signal data:1||memoization:1||Intelligent traffic control:1||Local outlier probability:1||Deep denoising autoencoder:1||Overhead hoist transport lifter:1||Depthfirst search:1||kmeans clustering:1||Label propagation:1||Gaussian process regression:1||Imbalanced class:1||Overlapping class:1||Datadriven optimization:1||Stochastic dynamic programming:1||Citation networks:1||Sports player evaluation:1||Customer review:1||High dimensionality:1||T2 decomposition:1||False discovery rate:1||Glutathione:1||Novelty Detection:1||neurodynamic programming:1||Malaria:1||Prostate cancer:1||Weapon systems:1||EWMA:1||online monitoring:1||Oneclass classification algorithm:1||Treesbased models:1||forklift:1||Mixedtype defect patterns:1||Classification algorithms:1||oversampling:1||Quality assessment:1||steel manufacturing:1||Deep learning:1||selfstarting forecasting:1||Markov processes:1||heuristic search algorithm:1||simulated annealing with a greedy algorithm:1||Graph structure:1||Semantic relationships:1||Graphbased clustering:1||Spectral clustering:1||Node cutting:1||modelfree method:1||deterministic policy gradient:1||classification algorithm:1||Genetic algorithm:1||sparse regularization:1||virtual metrology:1||ozone:1||decision tree algorithm:1||Contentbased filtering:1||Recommender system:1||text summarization:1||Multivariate process control:1||classification:1||Silhouette statistic:1||Multimodality:1||kNN:1||Change point detection:1||Multivariate EWMA:1||Nonhomogeneous change size:1||decision tree:1||support vector data description:1||novelty detection:1||Largescale optimization:1||Variable selection:1||Brain metabolism:1||Bootstrap Method:1||TFTLCD Process:1||Association Rule:1||Sexual assault:1||CUSUM:1||conditional expected delay:1||Attention mechanism:1||Context modeling:1||Manufacturing:1||Wafer bin maps:1||Consistency regularization:1||Generators:1||Correlation:1||root cause analysis (RCA):1||Statistical modeling:1||Random subspace method:1||Greedy algorithms:1||Discrete optimization:1||Autonomous vehicle systems:1||Expected model change maximization:1||Pseudodensity reconstruction:1||Reinforcement learning:1||Statistical process monitoring:1||Facility location problem:1||expert priors:1||temperature:1||Semisupervised classification:1||PCA:1||Movie recommendation:1||Network analysis:1||Selforganizing map:1||sentenceterm matrix:1||Wavelet transforms:1||Generalized likelihood ratios:1||oneclass classification:1||TFTLCD:1||Mahalanobis Distance:1||Multivariate process:1||cascade processes:1||Chemical oxygen demand:1||Trace evidence:1||Ionic liquids:1||Orthogonal Signal Correction:1||supervised classification method:1||Multiple criteria decision analysis:1||Analytic hierarchy process:1||semantic segmentation:1||AGV:1||multitask learning:1||explainable neural network:1||attention mechanism:1||de novo molecular design:1||remaining useful life regression:1||replacement simulation:1||Product design:1||Activation mapping:1||multisensor signal data:1||Ensemble importance score:1||Silhouette decomposition:1||Search problems:1||Convergence:1||Material handling:1||Phrase rankings:1||Highdimensional process:1||Vehicle lifter:1||process control:1||Mixedinteger quadratic programming:1||Fatty acid methyl esters:1||Cluster analysis:1||Nonstationary process:1||Design and analysis of computer experiments:1||text similarity measure:1||Classification algorithm:1||Time series:1||Wrapper:1||clustering algorithm:1||Nutritional assessment:1||Modelbased control chart:1||capacitated reentrant line:1||Matrixassisted laser desorption/ionization:1||Cuticular lipids:1||Multivariate Process:1||fault isolation:1||health surveillance:1||eating disorders:1||Multichannel signal:1||Multisensor signal:1||landcover classification:1||gasinsulated switchgear:1||Location awareness:1||Manufacturing processes:1||Bayes methods:1||Instruction sets:1||Hierarchical networks:1||Novelty detection:1||Variational autoencoder:1||machine learning:1||PM10:1||Best subset selection:1||Treebased ensemble:1||Microbial identification:1||Gas chromatography  vacuum ultraviolet spectroscopy:1||Gas phase absorption spectroscopy:1||Airport deicing:1||Recommender systems:1||Deep neural network:1||Sentence polarity:1||Fused lasso:1||Density coefficient:1||Random forest:1||Regression splines:1||Spatiotemporal surveillance:1||density:1||Regression trees:1||autocorrelated processes:1||data mining algorithms:1||Smoking patterns:1||Anopheles gambiae:1||Support vector machines:1||MALDITOFMS:1||Principal Component Analysis:1||Hotelling’s T^2:1||oneclass classification algorithm:1||data depth:1||Goal programming:1||Bayes classifier:1||diurnal variation:1||gastrointestinal regulation:1||unmanned aerial vehicles:1||Exemplar group detection:1||Recurrent neural networks:1||Semiconductor device modeling:1||generative adversarial networks:1||Safe semisupervised deep learning:1||Uncertain noise:1||Training data:1||selfsupervised learning:1||contrastive learning:1||Image reconstruction:1||comparative study:1||exponentially weighed moving average:1||Unsupervised feature ranking:1||parallel structure learning:1||Constrained regression:1||Nonlinear process:1||Semisupervised learning:1||Diversity:1||Quality:1||control:1||Semiconductor manufacturing:1||knowledge representation:1||relative humidity:1||Support vector machine:1||feature network:1||Mutual neighborhoodbased density coefficient:1||Noisy data clustering:1||Plasma etch:1||Spectroscopic signal:1||Recursive binary partitioning:1||Regularization:1||Forecasting:1||Multivariate CUSUM:1||Oxidative stress:1||Amino acid metabolism:1||Protein malnutrition:1||Autocorrelated process:1||principal component analysis:1||Text Mining:1||Mosquito:1||Condom lubricant:1||Mass Spectra:1||Preprocessing:1||support vector machines:1||temporal surveillance:1||Autocorrelated multivariate process:1||multivariate process:1||oneclass classification method:1||metabolomics:1||Multivariate time series:1||Swarm intelligence:1||Bayesian deep learning:1||Soft sensor:1||reinforcement learning:1||Mixup:1||remanufacturing:1||Generative adversarial networks:1||Predictive models:1||Fabrication:1||convolutional neural networks:1||Simulated annealing:1||Variable subset selection:1||multiagent cooperation:1||actorcritic method:1||Multiple linear regression:1||Consensus rate:1||Oneclass classification:1||Baseball:1||visualization:1||Maximizing connectivity:1||Lipid mass spectra:1||ARIMA:1||Gower distance:1||Mixture data:1||Multiple Normal Classes:1||Social Network Analysis:1||Airplane deicing and antiicing:1||Biological fluid:1||s T2 chart:1||Class imbalance:1||Near infrared:1||Poisson distribution:1||Explainable neural network:1||Swarm ascending:1||Multiple wafer bin maps classification:1||simplified molecularinput lineentry system (SMILES) strings:1||accelerated life testing:1||Bayesian neural network:1||generative model:1||multimodality:1||Object oriented modeling:1||qualitydiscriminative localization:1||

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