CS/Fundamentals
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Mathematical Statistics
2013.09.30
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Exponential family
2013.07.16
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Gibbs sampling
2013.07.02
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Probability and Distribution
2013.07.01
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Bayesian Statistics; 베이지안 통계학
2013.06.28
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Importance sampling
2013.06.21
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Metropolis-Hastings algorithm
2013.06.20
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Rejection sampling
2013.06.19
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Inverse transform sampling
2013.06.19
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Detailed Balance
2013.06.19
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통계학의 오늘
2013.05.25
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Kullback–Leibler divergence and Cross entropy
2013.05.20
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Probabilty and Bottleneck
2013.05.16
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Convex hull, Convex set, Convex combination, and Simplex
2013.05.15
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Helmholtz free energy
2013.05.11
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Boltzmann Machine
2013.05.11
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Simulated Annealing, 담금질 기법
2013.05.11
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Definition, Axiom, Theorem, Corollary, and Lemma
2013.04.28
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Tensor
2013.04.18
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Gram–Schmidt process
2013.04.11
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Eigendecomposition (Spectral Decomposition)
2013.04.10
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Linear Map (Linear Transformation)
2013.04.07
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Matrix Decomposition (Matrix Factorization)
2013.03.29
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Singular Value Decomposition, SVD
2013.03.28
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Entropy
2013.03.09
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Probability Density Function (PDF) and Probability Mass Function (PMF)
2013.03.08
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Lagrange Multipliers
2013.03.06
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Markov Chain Monte Carlo, MCMC
2013.02.27
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Normal distribution (Gaussian distribution)
2013.02.23
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Perron–Frobenius theorem
2013.02.08