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  • Crainiceanu Ciprian; Ruppert David; Claeskens Gerda; Wand Matt (Oxford University Press, 2005)
    Penalised-spline-based additive models allow a simple mixed model representation where the variance components control departures from linear models. The smoothing parameter is the ratio of the random-coefficient and error ...
  • Cheang Gerald; Chiarella Carl (Routledge, 2011)
    This article extends the exchange option model of Margrabe, where the distributions of both stock prices are log-normal with correlated Wiener components, to allow the underlying assets to be driven by jump-diffusion ...
  • Chen J; Duan Runyao; Ji Zhengfeng; Ying Mingsheng; Yu Jeffrey (Amer Inst Physics, 2008)
    A gate is called an entangler if it transforms some (pure) product states to entangled states. A universal entangler is a gate which transforms all product states to entangled states. In practice, a universal entangler is ...
  • Ormerod J.; Wand Matt (American Statistical Association, 2010)
    Variational approximations facilitate approximate inference for the parameters in complex statistical models and provide fast, deterministic alternatives to Monte Carlo methods. However, much of the contemporary literature ...
  • Mititelu Gabriel; Areepong Y; Sukparungsee S; Novikov Alex (Chiang Mai University, 2010)
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  • Borovkov Kostya; Novikov Alex (Applied Probability Trust, 2005)
    We give explicit upper bounds for convergence rates when approximating both one- and two-sided general curvilinear boundary crossing probabilities for the Wiener process by similar probabilities for close boundaries of ...
  • Pearce N.; Wand Matt (Institute of Mathematical Statistics, 2009)
    Two areas of research ¿ longitudinal data analysis and kernel machines ¿ have large, but mostly distinct, literatures. This article shows explicitly that both fields have much in common with each other. In particular, many ...
  • Lu Jie; Shi Chenggen; Zhou Hong; Zhang Guangquan (Elsevier, 2007)
    For linear bilevel programming, the branch and bound algorithm is the most successful algorithm to deal with the complementary constraints arising from Kuhn-Tucker conditions. However, one principle challenge is that it ...
  • Walker, S. G; Choy, S. (Elsevier Science, 2006)
    In this paper, it is demonstrated that an extension to the exponential power family allows for robustness characteristics for the normal location parameter problem, previously thought to be restricted to the Student-t and ...
  • Zhang Guangquan; Lu Jie; Steele Robert; Shi Chenggen (Joint Conference On Information Sciences, 2005)
    Organizational bilevel decision-making often involves uncertain factors. The parameters shown in a bilevel programming model, either in the objective functions or constraints, are thus often imprecise, which is called the ...
  • Lu Jie; Shi Chenggen; Zhang Guangquan (Elsevier Science, 2006)
    Kth-best approach is one of the three popular and workable approaches for linear bilevel programming. However, it could not well deal with a linear bilevel programming problem when the constraint functions at the upper-level ...
  • Lu Jie; Shi Chenggen; Zhang Guangquan (Elsevier Science, 2004)
    Kuhn-Tucker approach has been applied with remarkable success in linear bilevel programming (BLP). However, it still has some extent unsatisfactory and incomplete. One principle challenges is that it could not well handle ...
  • Melham Ray (University of Waterloo, Ontario, Canada, 2009)
    In 1987 Knopfmacher and Knopfmacher published new infinite product expansions for real numbers 0 < A < 1 and A > 1. They called these expansions Engel product expansions. At that time they had difficulty finding rational ...
  • Yeh Wei-Chang; Lin Wen-Ben; Hsieh Tsung-Jung; Liu Sin-Long (Pergamon-Elsevier Science Ltd, 2011)
    To construct the model of gene expression using microarray techniques can reveal the regulation rules from the gene expression profiles. From S-system model, it is able to analyze the regulatory system dynamics. However, ...
  • Bae Changseok; Yeh Wei-Chang; Chung Yuk; Liu Sin-Long (Pergamon-Elsevier Science Ltd, 2010)
    Data mining is the most commonly used name to solve problems by analyzing data already present in databases. Feature selection is an important problem in the emerging field of data mining which is aimed at finding a small ...
  • Ganguli Bhaswati; Wand Matt (Springer New York LLC, 2007)
    This paper develops inference for the significance of features such as peaks and valleys observed in additive modeling through an extension of the SiZer-type methodology of Chaudhuri and Marron (1999) and Godtliebsen et ...
  • Khushaba Rami N; Al-Ani Ahmed; Al-Jumaily Adel (Pergamon - Elsevier Ltd., 2011)
    One of the fundamental motivations for feature selection is to overcome the curse of dimensionality problem. This paper presents a novel feature selection method utilizing a combination of differential evolution (DE) ...
  • Chiarella Carl; Di Guilmi Corrado (Elsevier Inc, 2011)
    This paperexaminesthedynamicsoffinancialdistressandinparticularthemechanism of transmissionofshocksfromthefinancialsectortotherealeconomy.Theanalysisis performedbyrepresentingthelinkagesbetweenmicroeconomicfinancialvariablesand ...
  • Sutcliffe Paul; Solomon Andrew; Edwards Jennifer (WSEAS, 2007)
    We give a polynomial time algorithm to find the population variance of tour costs over the solution space of the symmetric Traveling Salesman Problem (TSP). In practical terms the algorithm provides a linear time method, ...
  • Elhouar Mikael (Routledge, 2008)
    This paper studies Heath-Jarrow-Morton-type models with regime-switching stochastic volatility. In this setting the forward rate volatility is allowed to depend on the current forward rate curve as well as on a continuous ...