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作者：Liang, Hua; Miao, Hongyu; Wu, Hulin
作者单位：University of Rochester
摘要：Modeling viral dynamics in HIV/AIDS studies has resulted in a deep understanding of pathogenesis of HIV infection from which novel antiviral treatment guidance and strategies have been derived. Viral dynamics models based on nonlinear differential equations have been proposed and well developed over the past few decades. However, it is quite challenging to use experimental or clinical data to estimate the unknown parameters (both constant and time-varying parameters) in complex nonlinear diffe...
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作者：Kolar, Mladen; Song, Le; Ahmed, Amr; Xing, Eric P.
作者单位：Carnegie Mellon University
摘要：Stochastic networks are a plausible representation of the relational information among entities in dynamic systems such as living cells or social communities. While there is a rich literature in estimating a static or temporally invariant network from observation data, little has been done toward estimating time-varying networks from time series of entity attributes. In this paper we present two new machine learning methods for estimating time-varying networks, which both build on a temporally...
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作者：Ghosh, Samiran
作者单位：Purdue University System; Purdue University; Purdue University in Indianapolis
摘要：This paper describes a novel approach based on proportional imputation when identical units produced in a batch have random but independent installation and failure times. The current problem is motivated by a real life industrial production-delivery supply chain where identical units are shipped after production to a third party warehouse and then sold at a future date for possible installation. Due to practical limitations, at any given time point, the exact installation as well as the failu...
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作者：Xu, Ya; Dyer, Justin S.; Owen, Art B.
作者单位：Stanford University
摘要：In semi-supervised learning on graphs, response variables observed at one node are used to estimate missing values at other nodes. The methods exploit correlations between nearby nodes in the graph. In this paper we prove that many such proposals are equivalent to kriging predictors based on a fixed covariance matrix driven by the link structure of the graph. We then propose a data-driven estimator of the correlation structure that exploits patterns among the observed response values. By incor...
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作者：Zanghi, Hugo; Picard, Franck; Miele, Vincent; Ambroise, Christophe
作者单位：Dassault Systemes; VetAgro Sup; Universite Claude Bernard Lyon 1; INRAE; Universite Paris Saclay; Centre National de la Recherche Scientifique (CNRS); CNRS - National Institute for Mathematical Sciences (INSMI)
摘要：In this paper we adapt online estimation strategies to perform model-based clustering on large networks. Our work focuses on two algorithms, the first based on the SAEM algorithm, and the second on variational methods. These two strategies are compared with existing approaches on simulated and real data. We use the method to decipher the connexion structure of the political websphere during the US political campaign in 2008. We show that our online EM-based algorithms offer a good trade-off be...
