ScholarWorks@Korea University: Koo, Ja Yong

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Koo, Ja Yong (구자용)

College of Political Science & Economics (Department of Statistics)

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Tel 2240
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Coordinate descent algorithm:5||Classification:3||HelgasonFourier transform:2||Sobolev ellipsoid:2||splines:2||Riemannian geometry:2||Variable selection:2||LaplaceBeltrami operator:2||classification:2||Oracle inequality:2||l(1) penalty:2||LASSO:2||Deconvolution:2||밀도 추정:2||Support vector machine:2||62F07:2||EM algorithm:2||62G08:2||BIC:2||Minimax adaptivity:1||Model selection consistency:1||Binary classification:1||decision curve:1||TCGA:1||fully datadriven procedure:1||supersmooth error:1||extrinsic mean:1||로지스틱회귀모형:1||bone pin and skin marker:1||lasso:1||persistent homology:1||Component selection and smoothing operator:1||Functional ANOVA decomposition:1||simulated annealing.:1||deconvolution:1||spectral decomposition:1||PinskerWeyl bound:1||discriminant analysis:1||adaptive choice:1||Weyl&apos:1||nonparametric density estimation:1||Knot selection:1||KullbackLeibler divergence:1||Logdensity estimation:1||Minimax rate:1||Total variation:1||augmented Lagrangian function:1||Common density:1||Binormal:1||structured kernel:1||Multidimensional scaling(MDS):1||bottleneck distance:1||HarishChandra cfunction:1||스플라인 분류 기계:1||분광 분해:1||legendre polynomials:1||kmeans clustering:1||local features:1||irreducible characters:1||weights:1||Gaussian mixture.:1||Tree model:1||Legendre polynomial basis:1||coordinate descent algorithm:1||Adaptive estimation:1||Primary: 62G10:1||SPD:1||임의변수선택:1||differential equations:1||functional ANOVA decomposition:1||Fisher consistency:1||Likelihood ratio test:1||functional data:1||cutpoint selection:1||Fourier analysis:1||upper halfplane:1||선택 확률:1||역문제:1||inverse Problem:1||kspatial medians clustering:1||Recovery process:1||credit risk:1||asymptotic normality:1||Bahadur representation:1||Spherical harmonics:1||gene function:1||Hellinger distance:1||EM 알고리즘:1||density estimation:1||나무모형:1||Optimal convergence rate:1||Wavelet basis:1||Metaanalysis:1||Density estimation:1||Semisupervised learning:1||ensemble method:1||normal:1||smooth curve:1||Quantum mechanics:1||topology:1||credit scoring:1||special linear group:1||density Estimation:1||coarse classification:1||constant spline:1||신용 위험:1||logistic regression:1||spline basis:1||Radon transform:1||Mixtures:1||Bspline basis:1||positive roots:1||분류:1||배경자료:1||Penalized likelihood:1||total variation:1||spherical deconvolution:1||Kmeans:1||Naive Bayes:1||random predictor selection:1||mean zscore:1||biomechanics:1||Qubit:1||Score test:1||persistence diagram:1||Manifold regularization:1||Cayley transform:1||hyperbolic space:1||Choice Probability:1||MISE:1||Outlier:1||판별 분석:1||Sobolev class:1||s formula:1||Cluster analysis:1||Isplines:1||Total variation penalty:1||Oracle inequalities:1||앙상블기법:1||tangent:1||Smoothly clipped absolute deviation:1||Maximum likelihood estimation:1||optimal rate:1||Mobius transformation:1||Spectral geometry:1||function estimation.:1||함수 추정.:1||simulated annealing:1||imputation:1||knearest neighbors:1||Fourier basis:1||fourier analysis on groups:1||irreducible representations:1||군집분석:1||Monotone regression:1||Binary method:1||Noncrossing:1||Penalized least squares:1||Data integration:1||nonparametric alternatives:1||solution path:1||Euclidean distance:1||geodesic distance:1||intrinsic mean:1||KOSPI:1||Model selection:1||logistic regression model:1||quadratic program:1||Multinomial distribution:1||stochastic volatility:1||Semisupervised learning:1||classification spline machine:1||모의 담금질:1||crossvalidation:1||Eigenstructure:1||Laplacian:1||Weyl constant:1||변수 성김화:1||convexity lemma:1||KleinNishina distribution:1||Pinsker theory:1||베이지안 정보량:1||정규 혼합분포.:1||Reference data:1||Reversearcing:1||maximum tuning parameter:1||Lasso:1||Maximum complexity parameter:1||Bspline:1||convergence rate:1||Weighted quantile:1||Secondary: 62H11:1||rotational harmonics:1||minimax hypothesis testing:1||analytic classes:1||stock data:1||평균 z스코어:1||knots:1||linear program:1||Oracle property:1||Poisson distribution:1||신용평점화:1||절단값 선택.:1||impedance:1||statistical inverse problems:1||르장드르 다항식:1||평균적분제곱오차:1||상수 스플라인:1||cutpoint:1||functional data classification:1||Penalized logdensity estimation:1||Cholesky decomposition:1||

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