The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Recently a network-constraint regression model[1] is proposed to incorporate the prior biological knowledge to perform regression and variable selection. In their method, a l1-norm of the coefficients is defined to impose sparse, meanwhile a Laplacian operation on the biological graph is designed to encourage smoothness of the coefficients along the network. However the grouping effect of their Laplacian...
Salient object segmentation is an important technique for many content based applications. This paper presents an unsupervised salient object segmentation method under the graph cut optimization framework. First, we exploit a kernel density estimation based saliency model to generate the saliency map, which provides the useful cues for object segmentation. Then we exploit the saliency map to adaptively...
Today's applications deal with multiple types of information: graph data to represent the relations between objects and attribute data to characterize single objects. Analyzing both data sources simultaneously can increase the quality of mining methods. Recently, combined clustering approaches were introduced, which detect densely connected node sets within one large graph that also show high similarity...
Community detection, as an important unsupervised learning problem in social network analysis, has attracted great interests in various research areas. Many objective functions for community detection that can capture the intuition of communities have been introduced from different research fields. Based on the classical single objective optimization framework, this paper compares a variety of these...
The modularity function is a widely used measure for the quality of a graph clustering. Finding a clustering with maximal modularity is NP-hard. Thus, only heuristic algorithms are capable of processing large datasets. Extensive literature on such heuristics has been published in the recent years. We present a fast randomized greedy algorithm which uses solely local information on gradients of the...
The paper is to propose a framework to qualitatively and quantitatively evaluate five of state-of-the-art over-segment approaches. Moreover upon over-segments evaluation, an efficient approach is developed for dense stereo matching through robust higher-order MRFs and graph cut based optimization, which combines the conventional data and smoothness terms with the robust higher-order potential term...
Multi-modality, the unique and important property of video data, is typically ignored in existing video adaptation processes. To solve this problem, we propose a novel approach, named multi-modality transfer based on multi- graph optimization (MMT-MGO) in this paper, which leverages multi-modality knowledge generalized by auxiliary classifiers in the source domain to assist multi-graph optimization...
A robust semi-supervised method using the mode filter has been presented for learning with partially-labeled training data including label errors. The mode filter has been originally developed for smoothing images contaminated with impulsive noises. However it needs nonlinear optimization which is usually solved with iterative methods. In this paper, we propose a direct solution method with full search...
With the increasing popularity and development of e-commerce and information technology, multi-attribute bilateral matching problem has been receiving more and more attention. In this paper, multi-attribute bilateral matching problem is discussed based on the consideration of stable matching. Concepts and definitions of multi-attribute bilateral stable matching are presented firstly, followed by the...
In practice, ad hoc networks are still too unreliable for standard mobile and vehicular communications. It is thus important to complement current protocols in this context, with schemes guaranteeing the exchange of critical data when needed. A promising approach in this realm is to use an overlay subgraph, over which critical messages are exchanged and acknowledged in a peer to peer fashion. Overlay...
For the shortcomings of course scheduling system, this paper builds a new mathematical model about College Course Scheduling, transforms the problem to exploring the biggest match problem of bipartite graph by using the superiority of ant colony algorithm in solving combinatorial optimization problems, gives an improved ant colony algorithm which can optimize the course scheduling algorithm, makes...
This paper presents a new method to extract foreground using Graph-cut on color and texture combination. Traditional graph-cut algorithm only used intensity at pixel level, this amount of information is insufficient for complex situations in which objects are camouflaged or in uneven exposure condition. Our method makes use of texture additionally from dense SIFT sampling to segment robustly hard...
The present paper develops a methodology to choose the best connection scheme for traction substations of a Massive Electrical Railway System (MERS) and distribution substations in urban areas using graph theory and economical optimization.
Reliability and/or availability are increasingly important aspects in the design of systems, especially networks and service offerings. Optimization here is a multi-criteria process finding the right compromise between cost and quality. At the same time, results should be explored online, either as part of interactive, user-centric design tools or for Web based service negotiation. In this paper we...
We present a Monte Carlo algorithm for Hamiltonicity detection in an n-vertex undirected graph running in O* (1.657n) time. To the best of our knowledge, this is the first superpolynomial improvement on the worst case runtime for the problem since the O*(2n) bound established for TSP almost fifty years ago (Bellman 1962, Held and Karp 1962). It answers in part the first open problem in Woeginger's...
It has been shown by Indyk and Sidiropoulos that any graph of genus g > 0 can be stochastically embedded into a distribution over planar graphs with distortion 2O(g). This bound was later improved to O(g2) by Borradaile, Lee and Sidiropoulos. We give an embedding with distortion O(log g), which is asymptotically optimal. Apart from the improved distortion, another advantage of our embedding is...
We give a subexponential time approximation algorithm for the Unique Games problem. The algorithms run in time that is exponential in an arbitrarily small polynomial of the input size, nε. The approximation guarantee depends on ε, but not on the alphabet size or the number of variables. We also obtain a subexponential algorithms with improved approximations for SMALL-SET EXPANSION and MULTICUT. For...
The balanced graph partitioning consists in dividing the vertices of an undirected graph into a given number of subsets of approximately equal size, such that the number of edges crossing the subsets is minimized. In this work, we present a multilevel memetic algorithm for this NP-hard problem that relies on a powerful grouping recombination operator and a dedicated local search procedure. The proposed...
Multi-agent systems have been proposed as a promising technology for addressing many problems in distributed information management, Internet and so on. Decomposing and allocating asks in MAS has proved to be a NP-hard question. The approach based on And/Or graph solving this question has been proposed and verified by simulation which offers a new way for tasks planning in MAS.
The Operation Characteristic analysis is one of the most important parts in Quality Inspection. However, the current quality inspection method system lacks a quantitative evaluation index and it only suits for single-factor-analysis of sampling plan. In this paper, a feasible evaluation indexes for operation characteristic curve is proposed based on the concept of Shannon's Entropy. Then, the Entropy...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.