共查询到20条相似文献,搜索用时 15 毫秒
1.
Jianhua Xu 《Expert systems with applications》2012,39(5):4796-4804
Existing multi-label support vector machine (Rank-SVM) has an extremely high computational complexity and lacks an intrinsic zero point to determine relevant labels. In this paper, we propose a novel support vector machine for multi-label classification through both simplifying Rank-SVM and adding a zero label, resulting into a quadratic programming problem in which each class has an independent equality constraint. When Frank-Wolfe method is used to solve our quadratic programming problem iteratively, our entire linear programming problem of each step is divided into a series of sub-problems, which dramatically reduces computational cost. It is illustrated that for famous Yeast data set our training procedure runs about 12 times faster than Rank-SVM does under C++ environment. Experiments from five benchmark data sets show that our method is a powerful candidate for multi-label classification, compared with five state-of-the-art multi-label classification techniques. 相似文献
2.
Multi-label core vector machine (Rank-CVM) is an efficient and effective algorithm for multi-label classification. But there still exist two aspects to be improved: reducing training and testing computational costs further, and detecting relevant labels effectively. In this paper, we extend Rank-CVM via adding a zero label to construct its variant with a zero label, i.e., Rank-CVMz, which is formulated as the same quadratic programming form with a unit simplex constraint and non-negative ones as Rank-CVM, and then is solved by Frank–Wolfe method efficiently. Attractively, our Rank-CVMz has fewer variables to be solved than Rank-CVM, which speeds up training procedure dramatically. Further, the relevant labels are effectively detected by the zero label. Experimental results on 12 benchmark data sets demonstrate that our method achieves a competitive performance, compared with six existing multi-label algorithms according to six indicative instance-based measures. Moreover, on the average, our Rank-CVMz runs 83 times faster and has slightly fewer support vectors than its origin Rank-CVM. 相似文献
3.
4.
冗余度机械臂的二次规划(QP)问题同时受制于等式约束、不等式约束和双端约束,且面向冗余度机械臂实时控制的该类QP问题的求解对运算实时性有较高要求。考虑同时受制于上述三种约束的二次规划问题的求解,给出并研究两种数值算法(E47和94LVI算法)。这类带约束的二次规划问题被等价转换为分段线性投影方程。应用E47和94LVI算法求解上述分段线性投影方程,从而得到二次规划问题的最优数值解。同时,通过大量的数值实验,研究两种算法面向冗余度机械臂的QP问题求解性能,并给出E47、94LVI算法与经典有效集算法的对比实验结果。最终证实了E47和94LVI两种算法在求解二次规划问题上的高效性和优越性。 相似文献
5.
Jianhua Xu Author Vitae 《Neurocomputing》2011,74(17):3114-3124
Hybrid strategy, which generalizes a specific single-label algorithm while one or two data decomposition tricks are applied implicitly or explicitly, has become an effective and efficient tool to design and implement various multi-label classification algorithms. In this paper, we extend traditional binary support vector machine by introducing an approximate ranking loss as its empirical loss term to build a novel support vector machine for multi-label classification, resulting into a quadratic programming problem with different upper bounds of variables to characterize label correlation of individual instance. Further, our optimization problem can be solved via combining one-versus-rest data decomposition trick with modified binary support vector machine, which dramatically reduces computational cost. Experimental study on ten multi-label data sets illustrates that our method is a powerful candidate for multi-label classification, compared with four state-of-the-art multi-label classification approaches. 相似文献
6.
目前多标签学习已广泛应用到很多场景中,在此类学习问题中,一个样本往往可以同时拥有多个类别标签。由于类别标签可能带有的特有属性(即类属属性)将更有助于标签分类,所以已经出现了一些基于类属属性的多标签学习算法。针对类属属性构造会导致属性空间存在冗余的问题,本文提出了一种多标签类属特征提取算法LIFT_RSM。该方法基于类属属性空间通过综合利用随机子空间模型及成对约束降维思想提取有效的特征信息,以达到提升分类性能的目的。在多个数据集上的实验结果表明:与若干经典的多标签算法相比,提出的LIFT_RSM算法能得到更好的分类效果。 相似文献
7.
A unified quadratic-programming-based dynamical system approach to joint torque optimization of physically constrained redundant manipulators 总被引:6,自引:0,他引:6
Yunong Zhang Ge S.S. Tong Heng Lee 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2004,34(5):2126-2132
In this paper, for joint torque optimization of redundant manipulators subject to physical constraints, we show that velocity-level and acceleration-level redundancy-resolution schemes both can be formulated as a quadratic programming (QP) problem subject to equality and inequality/bound constraints. To solve this QP problem online, a primal-dual dynamical system solver is further presented based on linear variational inequalities. Compared to previous researches, the presented QP-solver has simple piecewise-linear dynamics, does not entail real-time matrix inversion, and could also provide joint-acceleration information for manipulator torque control in the velocity-level redundancy-resolution schemes. The proposed QP-based dynamical system approach is simulated based on the PUMA560 robot arm with efficiency and effectiveness demonstrated. 相似文献
8.
杨红梅 《计算机工程与应用》2013,49(11):38-40
考虑了一类带有不等式和等式混合约束的半无限规划问题。通过运用极大熵方法,将多个约束条件的问题转化为单个约束条件的非线性规划模型,并提出了求解它的一个神经网络模型,严格证明了该模型是Lyapunov稳定的,并且在有限时间内收敛到原问题的一个精确解。数值实验表明,新模型不仅可行而且有效。 相似文献
9.
Statistical topic models for multi-label document classification 总被引:2,自引:0,他引:2
Timothy N. Rubin America Chambers Padhraic Smyth Mark Steyvers 《Machine Learning》2012,88(1-2):157-208
Machine learning approaches to multi-label document classification have to date largely relied on discriminative modeling techniques such as support vector machines. A?drawback of these approaches is that performance rapidly drops off as the total number of labels and the number of labels per document increase. This problem is amplified when the label frequencies exhibit the type of highly skewed distributions that are often observed in real-world datasets. In this paper we investigate a class of generative statistical topic models for multi-label documents that associate individual word tokens with different labels. We investigate the advantages of this approach relative to discriminative models, particularly with respect to classification problems involving large numbers of relatively rare labels. We compare the performance of generative and discriminative approaches on document labeling tasks ranging from datasets with several thousand labels to datasets with tens of labels. The experimental results indicate that probabilistic generative models can achieve competitive multi-label classification performance compared to discriminative methods, and have advantages for datasets with many labels and skewed label frequencies. 相似文献
10.
针对当前基于机器学习的早期阿尔茨海默病(AD)诊断中训练样本不足的问题,提出一种基于多模态特征数据的多标记迁移学习方法,并将其应用于早期阿尔茨海默病诊断。所提方法框架主要包括两大模块:多标记迁移学习特征选择模块和多模态多标记分类回归学习器模块。首先,通过稀疏多标记学习模型对分类和回归学习任务进行有效结合;然后,将该模型扩展到来自多个学习领域的训练集,从而构建出多标记迁移学习特征选择模型;接下来,针对异质特征空间的多模态特征数据,采用多核学习技术来组合多模态特征核矩阵;最后,为了构建能同时用于分类与回归的学习模型,提出多标记分类回归学习器,从而构建出多模态多标记分类回归学习器。在国际老年痴呆症数据库(ADNI)进行实验,分类轻度认知功能障碍(MCI)最高平均精度为79.1%,预测神经心理学量表测试评分值最大平均相关系数为0.727。实验结果表明,所提多模态多标记迁移学习方法可以有效利用相关学习领域训练数据,从而提高早期老年痴呆症诊断性能。 相似文献
11.
现有的类属属性学习方法在提取类别标签的特征时,大多仅单一考虑标签间的相关性,忽略实例和实例间以及特征与特征间的相关性,可能会降低分类精度.为了解决此问题,文中设计多类别相关性结合的类属属性多标签学习算法,考虑标签相关性、特征相关性和实例相关性.利用标签之间的余弦相似度计算标签相关性,构建相似图矩阵计算特征相关性和实例相关性.文中算法紧凑地选择标签的类属属性,提高分类精度,有效解决多标签分类遇到的维度过大问题. 相似文献
12.
Arti Singh Selvamuthu Dharmaraja 《International Transactions in Operational Research》2020,27(3):1771-1803
This paper studies the optimal portfolio trading problem under the generalized second‐order autoregressive execution price model. The problem of minimizing expected execution cost under the proposed price model is formulated as a quadratic programming (QP) problem. For a risk‐averse trader, problem formulation under the second‐order stochastic dominance constraints results in a quadratically constrained QP problem. Under some conditions on the execution price model, it is proved that the portfolio trading problems for risk‐neutral and risk‐averse traders become convex programming problems, which have many theoretical and computational advantages over the general class of optimization problems. Extensive numerical illustrations are provided, which render the practical significance of the proposed execution price model and the portfolio trading problems. 相似文献
13.
A New Optimal Force Distribution Scheme of Multiple Cooperating Robots Using Dual Method 总被引:1,自引:0,他引:1
A new optimal force distribution scheme of multiple cooperating robots is proposed, in which the duality theory of nonlinear programming (NLP) is combined with the quadratic programming (QP) approach. The optimal force distribution problem is formulated as a QP problem with both linear and quadratic constraints, and its solution is obtained by an efficient algorithm. The use of the quadratic constraints is important in that it considerably reduces the number of constraints, thus enabling the Dual method of NLP to be used in the solution algorithm. Moreover, it can treat norm constraints without approximation, such as bound of the norm of the force exerted by each robot. The proposed scheme is more efficient in terms of speed than any other method. Numerical examples of two PUMA robot task using the proposed method and a well-known fast method are compared, and the results indicate the capability of real time application of our method. 相似文献
14.
The paper presents a flexible and efficient modeling approach to the simulation of the folding process of general crease patterns. The development of the model has been motivated by the need to provide support for targeted design and efficient manufacturing of shell structures inspired by the origami technique. This type of structures is becoming increasingly popular in many engineering disciplines and has been referred to as origamics. In the present work the folding technique is used to produce spatial structures from continuously reinforced thin-walled cementitious composite plates without the need to construct curved spatial formworks. In order to support the targetted design and manufacturing of folded concrete (oricrete) structures numerical model has been formulated as an optimization framework with several types of optimality conditions and equality constraints. The model is used both for form-finding of the spatial structure and for the realization of the manufacturing process. 相似文献
15.
Hiroyuki Tamura 《Automatica》1977,13(4):369-376
A multistage decomposition scheme is developed for optimizing discrete-time dynamic systems, which include distributed and/or multiple pure delays. The discrete optimal control problem in this paper consists of a system dynamics described by a multidimensional linear difference equation of high-order which is called the distributed-lag model, a linear objective function, and linear state and control constraints. This problem may be solved as a linear program by, for example, a revised simplex method. However, this leads to excessive storage requirement for large problems. Instead, by taking advantage of the staircase-structure of equality constraints (system equation), Dantzig-Wolfe decomposition principle is applied repeatedly in each stage, and an effective multistage decomposition algorithm for distributed-lag models is obtained. Significant advantage of the optimization technique in this paper is that it can handle any number of delay terms in the system without reducing the multidimensional high-order system equation to a conventional larger dimensional first-order system equation (state equation of normal form). Therefore, a substantial reduction of computational burden, the so called curse of dimensionality, in the existing discrete optimal control algorithms, is obtained. A numerical example of a congested urban road traffic control problem with many delays is included. 相似文献
16.
17.
This paper proposes a quadratic programming (QP) approach to robust model predictive control (MPC) for constrained linear systems having both model uncertainties and bounded disturbances. To this end, we construct an additional comparison model for worst-case analysis based on a robust control Lyapunov function (RCLF) for the unconstrained system (not necessarily an RCLF in the presence of constraints). This comparison model enables us to transform the given robust MPC problem into a nominal one without uncertain terms. Based on a terminal constraint obtained from the comparison model, we derive a condition for initial states under which the ultimate boundedness of the closed loop is guaranteed without violating state and control constraints. Since this terminal condition is described by linear constraints, the control optimization can be reduced to a QP problem. 相似文献
18.
19.
基于浮动阈值分类器组合的多标签分类算法 总被引:1,自引:0,他引:1
针对目标可以同时属于多个类别的多标签分类问题,提出了一种基于浮动阈值分类器组合的多标签分类算法.首先,分析探讨了基于浮动阈值分类器的AdaBoost算法(AdaBoost.FT)的原理及错误率估计,证明了该算法能克服固定分段阈值分类器对分类边界附近点分类不稳定的缺点从而提高分类准确率;然后,采用二分类(BR)方法将该单标签学习算法应用于多标签分类问题,得到基于浮动阈值分类器组合的多标签分类方法,即多标签AdaBoost.FT.实验结果表明,所提算法的平均分类精度在Emotions数据集上比AdaBoost.MH、ML-kNN、RankSVM这3种算法分别提高约4%、8%、11%;在Scene、Yeast数据集上仅比RankSVM低约3%、1%.由实验分析可知,在不同类别标记之间基本没有关联关系或标签数目较少的数据集上,该算法均能得到较好的分类效果. 相似文献
20.
由于标签空间过大,标签分布不平衡问题在多标签数据集中广泛存在,解决该问题在一定程度上可以提高多标签学习的分类性能.通过标签相关性提升分类性能是解决该问题的一种最常见的有效策略,众多学者进行了大量研究,然而这些研究更多地是采用基于正相关性策略提升性能.在实际问题中,除了正相关性外,标签的负相关性也可能存在,如果在考虑正相... 相似文献