Maximum entropy models and subjective interestingness: an application to tiles in binary databases

Recent research has highlighted the practical benefits of subjective interestingness measures, which quantify the novelty or unexpectedness of a pattern when contrasted with any prior information of the data miner (Silberschatz and Tuzhilin, Proceedings of the 1st ACM SIGKDD international conference on Knowledge discovery and data mining (KDD95), 1995; Geng and Hamilton, ACM Comput Surv 38(3):9, 2006). A key challenge here is the formalization of this prior information in a way that lends itself to the definition of a subjective interestingness measure that is both meaningful and practical. In this paper, we outline a general strategy of how this could be achieved, before working out the details for a use case that is important in its own right. Our general strategy is based on considering prior information as constraints on a probabilistic model representing the uncertainty about the data. More specifically, we represent the prior information by the maximum entropy (MaxEnt) distribution subject to these constraints. We briefly outline various measures that could subsequently be used to contrast patterns with this MaxEnt model, thus quantifying their subjective interestingness. We demonstrate this strategy for rectangular databases with knowledge of the row and column sums. This situation has been considered before using computation intensive approaches based on swap randomizations, allowing for the computation of empirical p-values as interestingness measures (Gionis et al., ACM Trans Knowl Discov Data 1(3):14, 2007). We show how the MaxEnt model can be computed remarkably efficiently in this situation, and how it can be used for the same purpose as swap randomizations but computationally more efficiently. More importantly, being an explicitly represented distribution, the MaxEnt model can additionally be used to define analytically computable interestingness measures, as we demonstrate for tiles (Geerts et al., Proceedings of the 7th international conference on Discovery science (DS04), 2004) in binary databases.     

Temporal kernel CCA and its application in multimodal neuronal data analysis

Data recorded from multiple sources sometimes exhibit non-instantaneous couplings. For simple data sets, cross-correlograms may reveal the coupling dynamics. But when dealing with high-dimensional multivariate data there is no such measure as the cross-correlogram. We propose a simple algorithm based on Kernel Canonical Correlation Analysis (kCCA) that computes a multivariate temporal filter which links one data modality to another one. The filters can be used to compute a multivariate extension of the cross-correlogram, the canonical correlogram, between data sources that have different dimensionalities and temporal resolutions. The canonical correlogram reflects the coupling dynamics between the two sources. The temporal filter reveals which features in the data give rise to these couplings and when they do so. We present results from simulations and neuroscientific experiments showing that tkCCA yields easily interpretable temporal filters and correlograms. In the experiments, we simultaneously performed electrode recordings and functional magnetic resonance imaging (fMRI) in primary visual cortex of the non-human primate. While electrode recordings reflect brain activity directly, fMRI provides only an indirect view of neural activity via the Blood Oxygen Level Dependent (BOLD) response. Thus it is crucial for our understanding and the interpretation of fMRI signals in general to relate them to direct measures of neural activity acquired with electrodes. The results computed by tkCCA confirm recent models of the hemodynamic response to neural activity and allow for a more detailed analysis of neurovascular coupling dynamics.     

Array SSL VPN如何保障番禺有线办公网的安全运行

企业办公自动化系统的应用十分广泛,随着互联网的高速发展,WEB应用成为主流,OA系统在互联网上的延伸成为大趋势,本文阐述在WEB应用中如何保障数据和系统安全的手段和方法。     

Exponential stability and exponential stabilization of singularly perturbed stochastic systems with time‐varying delay

In this paper, the problems of exponential stability and exponential stabilization for linear singularly perturbed stochastic systems with time‐varying delay are investigated. First, an appropriate Lyapunov functional is introduced to establish an improved delay‐dependent stability criterion. By applying free‐weighting matrix technique and by equivalently eliminating time‐varying delay through the idea of convex combination, a less conservative sufficient condition for exponential stability in mean square is obtained in terms of ε‐dependent linear matrix inequalities (LMIs). It is shown that if this set of LMIs for ε=0 are feasible then the system is exponentially stable in mean square for sufficiently small ε?0. Furthermore, it is shown that if a certain matrix variable in this set of LMIs is chosen to be a special form and the resulting LMIs are feasible for ε=0, then the system is ε‐uniformly exponentially stable for all sufficiently small ε?0. Based on the stability criteria, an ε‐independent state‐feedback controller that stabilizes the system for sufficiently small ε?0 is derived. Finally, numerical examples are presented, which show our results are effective and useful. Copyright © 2010 John Wiley & Sons, Ltd.     

一种无线传感器网络数据安全免疫体系结构

LEACH协议是提出较早、较为完整的无线传感器网络协议之一。在LEACH协议的基础上,借鉴生物免疫系统的原理,提出了一种新的适用于无线传感器网络的免疫体系结构。为构建这个体系,提出了基于覆盖面的备份簇头选举算法,嵌入数字基因的免疫应答算法,以及各状态节点的转换机制。备份簇头的引入,大大降低了恶意簇头对整个簇造成的破坏,免疫应答算法通过各功能节点的相互协作,能够有效地抵御恶意节点的攻击,减小和消除恶意数据的影响。仿真验证了该体系的有效性,在提高了安全性的同时,并不影响网络的生命期。     

城市综合管理"大联动"系统软件构架研究与实践

城市综合管理包括城市日常管理与应急事务处理两大部分,与城市治安相互补充.以闵行区大联动中心系统建设为依据,从大联动系统的业务流程、组织管理、技术路线等方面,进行系统的论述与总结,并对其中一些关键的技术环节和技术难点进行了探讨与研究.     

快速求解一类Toeplitz循环三对角线性方程组的分布式并行算法

在分布式存储环境下,提出了一种在给定误差范围内快速求解一类Toeplitz循环三对角线性方程组的分布式并行算法,该算法是在仔细研究了方程组结构特点的基础上,通过求解满足给定误差范围的方程组的近似解,从而使得通信开销小,冗余计算量少,数值试验表明：该算法具有较高的加速比和并行效率。     

Exact optimal solution for a class of dual control problems

This paper considers a discrete-time stochastic optimal control problem for which only measurement equation is partially observed with unknown constant parameters taking value in a finite set of stochastic systems. Because of the fact that the cost-to-go function at each stage contains variance and the non-separability of the variance is so complicated that the dynamic programming cannot be successfully applied, the optimal solution has not been found. In this paper, a new approach to the optimal solution is proposed by embedding the original non-separable problem into a separable auxiliary problem. The theoretical condition on which the optimal solution of the original problem can be attained from a set of solutions of the auxiliary problem is established. In addition, the optimality of the interchanging algorithm is proved and the analytical solution of the optimal control is also obtained. The performance of this controller is illustrated with a simple example.     

压缩感知中的信号重构方法分析

压缩感知理论(CS)因高采样速率和巨大的存储空间被广泛应用于认知无线电中.重构算法是压缩感知理论的核心之一,也是目前的研究热点.介绍了压缩感知理论的基本模型和重构算法,在基本的梯度算法(GP)基础上做了改进,提出了巴兹莱一伯文(PBB)算法,并对两种重构算法进行了仿真.仿真结果表明,PBB算法能更好地重构信号.     

在教学网上实现上机操作无纸考试及自动阅卷

在计算机相关课程的教学中 ,为了更好地考查学生的实际动手能力 ,实行上机操作考试无疑是一种非常有效的方法。而探讨如何在教学网上 ,真正实现无纸的上机操作考试 ,以及试后的自动阅卷 ,则更有其现实意义。为此 ,我们编制并调试成功了几个程序 ,实验效果良好 ,而其中的基本操作考试部分较具普遍性和通用性。1　实现方法1.1　准备工作 :1.作学员帐户 :在教学网上 (以ＮＥＴＷＡＲＥ3.12网为例 ) ,为各学员建立其个人帐户及各自的用户目录 ,并赋予应有的权限。例如 ,为学号是 96 0 5 10 1的学员建立帐户 96 0 5 10 1;设其个人目录在ＨＭ1卷上…