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.
This paper compares the performance improvement in recognition rate of different face recognition methods. The face recognition methods such as 1dPCA, 2dPCA, KPCA, ICA and FDA usually use Euclidean distance and in some cases they use the cosine similarity function. Instead of traditional classification and distance measurement methods, SVM classifier is used for classification. The SVM classifier...
In various applications where the problem domain can be modeled into graphs, the shortest path computation in the graph is an indispensable challenge. In applications like online social networks and shortest route computation problems, the size of the graph is so large; the number of nodes have become close to hundreds of billions. Shortest path graph algorithms like SSSP (Single Source Shortest Path)...
In this contribution, we propose a kernel-based method for the identification of linear systems from noisy and incomplete input-output datasets. We model the impulse response of the system as a Gaussian process whose covariance matrix is given by the recently introduced stable spline kernel. We adopt an empirical Bayes approach to estimate the posterior distribution of the impulse response given the...
Illumination condition is one of the most important factors that affect the face recognition performance. Face image illumination quality assessment can predict the face recognition performance under various illumination conditions, which will improve the accuracy and efficiency of the face recognition system. However, the quality scores calculated by the existing methods are weakly correlated with...
The P300 Speller is a Brain Computer Interface that enables communication using the EEG signal. The P300 wave is an Event Related Potential that occurs as a response to a familiar stimulus. This system can be used to aid persons who are unable to communicate via conventional methods. In this paper, the P300 Speller has been modified to allow communication in three languages: English, Sinhala and Tamil...
In this paper, we develop a new transitive aligned Weisfeiler-Lehman subtree kernel. This kernel not only overcomes the shortcoming of ignoring correspondence information between isomorphic substructures that arises in existing R-convolution kernels, but also guarantees the transitivity between the correspondence information that is not available for existing matching kernels. Our kernel outperforms...
Bai and Hancock recently proposed a novel edge-based matching kernel for graphs [1], by aligning depth-based representations. Unfortunately, one drawback arising in their kernel is the computational inefficiency for large graphs. This follows the fact that their kernel is essentially defined on directed line graphs. Moreover, the computational complexity of the kernel is cubic in the vertex number...
Kernel-based K-means clustering has gained popularity due to its simplicity and the power of its implicit non-linear representation of the data. A dominant concern is the memory requirement since memory scales as the square of the number of data points. We provide a new analysis of a class of approximate kernel methods that have more modest memory requirements, and propose a specific one-pass randomized...
Domain adaptation (DA) aims to eliminate the difference between the distribution of labeled source domain on which a classifier is trained and that of unlabeled or partly labeled target domain to which the classifier is to be applied. Compared with the semi-supervised domain adaptation where some labeled data from target domain is utilized to help train the classifier, the unsupervised domain adaptation...
Training kernel SVM on large datasets suffers from high computational complexity and requires a large amount of memory. However, a desirable property of SVM is that its decision function is solely determined by the support vectors, a subset of training examples with non-vanishing weights. This motivates a novel efficient algorithm for training kernel SVM via support vector identification. The efficient...
The ability of a human being to extrapolate previously gained knowledge to other domains inspired a new family of methods in machine learning called transfer learning. Transfer learning is often based on the assumption that objects in both target and source domains share some common feature and/or data space. In this paper, we propose a simple and intuitive approach that minimizes iteratively the...
In this paper, we introduce algorithms for pruning and aging user ratings in collaborative filtering systems, based on their oldness, under the rationale that aged user ratings may not accurately reflect the current state of users regarding their preferences. The aging algorithm reduces the importance of aged ratings, while the pruning algorithm removes them from the database. The algorithms are evaluated...
How to make a decision is a critical problem in speaker verification system and it directly affects the final verification results. This paper describes a new efficient threshold setting method that performs speaker verification system with I-vector technique. Unlike typical system under laboratory, it is difficult to obtain a large number of data to fully estimate the speaker recognition threshold...
Configuring an Evolutionary Algorithm (EA) can be a haphazard and inefficient process. An EA practitioner may have to choose between a plethora of search operator types and other parameter settings. In contrast, the goal of EA principled design is a more streamlined and systematic design methodology, which first seeks to better understand the problem domain, and only then uses such acquired insights...
We introduce a kernel formulation of the recently proposed minimum density hyperplane approach to clustering. This enables the identification of clusters that are not linearly separable in the input space by mapping them into a feature space. This mapping also extends the applicability of the minimum density hyperplane to datasets whose features are not necessarily continuous. The location of minimum...
Future avionics is no longer mere close electronic systems with the requirement changed, while it is pervasively controlled by dozens of frequent information exchange, open architecture and highly automatic systems. And this transformation has driven major advancements of security in avionics which contains computing security and communication security. Our team is focused on the security of next...
In this paper, we study the effects of using smoothed variance estimates in place of the sample variances on the performance of stochastic kriging (SK). Different variance estimation methods are investigated and it is shown through numerical examples that such a replacement leads to improved predictive performance of SK. An SK-based dual metamodeling approach is further proposed to obtain an efficient...
Automatic Question Answering (QA) is a hot topic in both Natural Language Processing (NLP) and Information Retrieval (IR). And question classification is the key step of a successful automatic QA system. In this paper, an SVM-based approach is firstly proposed as our baseline system. Then two additional features, i.e., top-words and dependency relations, are introduced to improve the performance of...
The word-level sentiment analysis is an essential issue in opinion mining. One challenge in this field is that not so many lexical items as expected have been labeled with sentimental opinions, especially in Chinese. There are two ways of rating words: one is manual marking which costs lots of resources, energy and time; the other is machine marking which is efficient, convenient and time-saving....
This article introduces a spectral method for statistical subspace clustering. The method is built upon standard kernel spectral clustering techniques, however carefully tuned by theoretical understanding arising from random matrix findings. We show in particular that our method provides high clustering performance while standard kernel choices provably fail. An application to user grouping based...
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.