1,082 research outputs found
On Bayesian Oracle Properties
When model uncertainty is handled by Bayesian model averaging (BMA) or
Bayesian model selection (BMS), the posterior distribution possesses a
desirable "oracle property" for parametric inference, if for large enough data
it is nearly as good as the oracle posterior, obtained by assuming
unrealistically that the true model is known and only the true model is used.
We study the oracle properties in a very general context of quasi-posterior,
which can accommodate non-regular models with cubic root asymptotics and
partial identification. Our approach for proving the oracle properties is based
on a unified treatment that bounds the posterior probability of model
mis-selection. This theoretical framework can be of interest to Bayesian
statisticians who would like to theoretically justify their new model selection
or model averaging methods in addition to empirical results. Furthermore, for
non-regular models, we obtain nontrivial conclusions on the choice of prior
penalty on model complexity, the temperature parameter of the quasi-posterior,
and the advantage of BMA over BMS.Comment: 31 page
Performance Analysis of Modified SRPT in Multiple-Processor Multitask Scheduling
In this paper we study the multiple-processor multitask scheduling problem in
both deterministic and stochastic models. We consider and analyze Modified
Shortest Remaining Processing Time (M-SRPT) scheduling algorithm, a simple
modification of SRPT, which always schedules jobs according to SRPT whenever
possible, while processes tasks in an arbitrary order. The M-SRPT algorithm is
proved to achieve a competitive ratio of for
minimizing response time, where denotes the ratio between maximum job
workload and minimum job workload, represents the ratio between maximum
non-preemptive task workload and minimum job workload. In addition, the
competitive ratio achieved is shown to be optimal (up to a constant factor),
when there are constant number of machines. We further consider the problem
under Poisson arrival and general workload distribution (\ie, system),
and show that M-SRPT achieves asymptotic optimal mean response time when the
traffic intensity approaches , if job size distribution has finite
support. Beyond finite job workload, the asymptotic optimality of M-SRPT also
holds for infinite job size distributions with certain probabilistic
assumptions, for example, system with finite task workload
Translation of Jiuzhaigou Tourism Websites From the Perspective of Eco-translatology
Taking Jiuzhaigou tourism website as an example and Eco-translatology as guidance theory, this paper analyzes the tourism text from language, cultural and communicative dimensions to obtain suggestions for tourism text translation. In translating tourism text, translator should simplify language and adjust sequence of text in language dimension, add supplementary information of culture elements in cultural dimension, and use more second person pronoun and interrogative sentences in communicative dimension. Thus, the translation can be more acceptable to target readers so as to achieve commercial purpose of tourism text
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