对Android平台电子节目指南(Electronic Program Guide,EPG)的总体设计与实现进行研究,用Android的SQLite数据库引擎分离节目索引和节目预告信息,对显示节目预告信息采用Java本地调用的数据获取方案并进行优化设计。实验结果表明,优化后方案明显地缩减了用户多次进入EPG业务的等待时间,界面友好,业务稳定性高,大幅提升了用户的服务体验。
This paper proposes a novel approach, Markov Chain Monte Carlo (MCMC) sampling approximation, to deal with intractable high-dimension integral in the evidence framework applied to Support Vector Regression (SVR). Unlike traditional variational or mean field method, the proposed approach follows the idea of MCMC, firstly draws some samples from the posterior distribution on SVR's weight vector, and then approximates the expected output integrals by finite sums. Experimental results show the proposed approach is feasible and robust to noise. It also shows the performance of proposed approach and Relevance Vector Machine (RVM) is comparable under the noise circumstances. They give better robustness compared to standard SVR.
