Browsing by Author "Hwang, Chii-Ruey"
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Item type:Item, Asymptotic error bounds for kernel-based Nystrom low-rank approximation matrices(2013-09-01) ;Chang, Lo-Bin ;Bai, Zhidong ;Huang, Su-Yun ;Hwang, Chii-Ruey應用數學系Many kernel-based learning algorithms have the computational load scaled with the sample size n due to the column size of a full kernel Gram matrix K. This article considers the Nystrom low-rank approximation. It uses a reduced kernel (K) over cap, which is n x m, consisting of m columns (say columns i(1), i(2),..., i(m)) randomly drawn from K. This approximation takes the form K approximate to (K) over capU(-1)(K) over cap (T), where U is the reduced m x m matrix formed by rows, i(1),i(2),..., i(m) of (K) over cap. Often m is much smaller than the sample size n resulting in a thin rectangular reduced kernel, and it leads to learning algorithms scaled with the column size m. The quality of matrix approximations can be assessed by the closeness of their eigenvalues and eigenvectors. In this article, asymptotic error bounds on eigenvalues and eigenvectors are derived for the Nystrom low-rank approximation matrix. (C) 2013 Elsevier Inc. All rights reserved.Item type:Item, Disorder Chaos in the Spherical Mean-Field Model(2015-07-01) ;Chen, Wei-Kuo ;Hsieh, Hsi-Wei ;Hwang, Chii-Ruey ;Sheu, Yuan-Chung應用數學系We study the problem of disorder chaos in the spherical mean-field model. It concerns the behavior of the overlap between two independently sampled spin configurations from two Gibbs measures with the same external parameters. The prediction states that if the disorders in the Hamiltonians are slightly decoupled, then the overlap will be concentrated near a constant value. Following Guerra\'s replica symmetry breaking scheme, we establish this at the levels of the free energy and the Gibbs measure.Item type:Item, Invariance in the recurrence of large returns and the validation of models of price dynamics(2013-08-09) ;Chang, Lo-Bin ;Geman, Stuart ;Hsieh, Fushing ;Hwang, Chii-Ruey應用數學系Starting from a robust, nonparametric definition of large returns ("excursions"), we study the statistics of their occurrences, focusing on the recurrence process. The empirical waiting-time distribution between excursions is remarkably invariant to year, stock, and scale (return interval). This invariance is related to self-similarity of the marginal distributions of returns, but the excursion waiting-time distribution is a function of the entire return process and not just its univariate probabilities. Generalized autoregressive conditional heteroskedasticity (GARCH) models, market-time transformations based on volume or trades, and generalized (Levy) random-walk models all fail to fit the statistical structure of excursions.