55 Result(s)
within
**u Tao
Computer Science
English
Computation by Abstract Devices
Data Mining and Knowledge Discovery
Image Processing and Computer Vision
Pattern Recognition
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Chapter and Conference Paper
Yet Another Schatten Norm for Tensor Recovery
In this paper, we introduce a new class of Schatten norms for tensor recovery. In the new norm, unfoldings of a tensor along not only every single order but also all combinations of orders are taken into accou...
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Chapter and Conference Paper
A Swarm Intelligence Algorithm Inspired by Twitter
For many years, evolutionary computation researchers have been trying to extract the swarm intelligence from biological systems in nature. Series of algorithms proposed by imitating animals’ behaviours have es...
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Chapter and Conference Paper
The Usability of Metadata for Android Application Analysis
The number of security incidents faced by Android users is growing, along with the surge in malware targeting Android terminals. Such malware arrives at the Android terminals in the form of Android Packages (A...
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Chapter and Conference Paper
Incremental Robust Nonnegative Matrix Factorization for Object Tracking
Nonnegative Matrix Factorization (NMF) has received considerable attention in visual tracking. However noises and outliers are not tackled well due to Frobenius norm in NMF’s objective function. To address thi...
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Chapter and Conference Paper
Time Series Classification Based on Multi-codebook Important Time Subsequence Approximation Algorithm
This paper proposes a multi-codebook important time subsequence approximation (MCITSA) algorithm for time series classification. MCITSA generates a codebook using important time subsequences for each class bas...
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Chapter and Conference Paper
Learning a Discriminative Dictionary with CNN for Image Classification
In this paper, we propose a novel framework for image recognition based on an extended sparse model. First, inspired by the impressive results of CNN over different tasks in computer vision, we use the CNN mod...
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Chapter and Conference Paper
Single-Frame Super-Resolution via Compressive Sampling on Hybrid Reconstructions
It is well known that super-resolution (SR) is a difficult problem, especially the single-frame super-resolution (SFSR). In this paper, we propose a novel SFSR method, called compressive sampling on hybrid rec...
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Chapter and Conference Paper
Matrix-Completion-Based Method for Cold-Start of Distributed Recommender Systems
Recommender systems has been wildly used in many websites. These perform much better on users for which they have more information. Satisfying the needs of users new to a system has become an important problem...
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Chapter and Conference Paper
Fine-Grained Risk Level Quantication Schemes Based on APK Metadata
The number of security incidents faced by Android users is growing, along with a surge in malware targeting Android terminals. Such malware arrives at the Android terminals in the form of Android Packages (APK...
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Chapter and Conference Paper
Adaptive DDoS-Event Detection from Big Darknet Traffic Data
This paper presents an adaptive large-scale monitoring system to detect Distributed Denial of Service (DDoS) attacks whose backscatter packets are observed on the darknet (i.e., unused IP space). To classify D...
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Chapter and Conference Paper
A Novel \(\ell ^1\) -graph Based Image Classification Algorithm
In original sparse representation based classification algorithms, each training sample belongs to exactly one class, neglecting the association between the training sample and the other classes. However, diff...
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Chapter and Conference Paper
Exploiting Latent Relations Between Users and Items for Collaborative Filtering
As one of the most important techniques in recommender systems, collaborative filtering (CF) generates the recommendations or predictions based on the observed preferences. Most traditional recommender systems...
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Chapter and Conference Paper
MonkeyDroid: Detecting Unreasonable Privacy Leakages of Android Applications
Static and dynamic taint-analysis approaches have been developed to detect the processing of sensitive information. Unfortunately, faced with the result of analysis about operations of sensitive information, p...
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Chapter and Conference Paper
Learning Task Specific Distributed Paragraph Representations Using a 2-Tier Convolutional Neural Network
We introduce a type of 2-tier convolutional neural network model for learning distributed paragraph representations for a special task (e.g. paragraph or short document level sentiment analysis and text topic ...
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Chapter and Conference Paper
An Ontology-Based Approach to Query Suggestion Diversification
Query suggestion is proposed to generate alternative queries and help users explore and express their information needs. Most existing query suggestion methods generate query suggestions based on document info...
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Chapter and Conference Paper
Exploiting Level-Wise Category Links for Semantic Relatedness Computing
Explicit Semantic Analysis(ESA) is an effective method that adopts Wikipedia articles to represent text and compute semantic relatedness(SR). Most related studies do not take advantage of the semantics carried...
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Chapter and Conference Paper
Multi-document Summarization Based on Sentence Clustering
A main task of multi-document summarization is sentence selection. However, many of the existing approaches only select top ranked sentences without redundancy detection. In addition, some summarization approa...
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Chapter and Conference Paper
Detecting Malicious Spam Mails: An Online Machine Learning Approach
Malicious spam is one of the major problems of the Internet nowadays. It brings financial damage to companies and security threat to governments and organizations. Most recent spam emails contain URLs that red...
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Chapter and Conference Paper
Forecasting Crowd State in Video by an Improved Lattice Boltzmann Model
Fluid methods have been introduced to analysis of crowd movements in videos recent years. Among these methods, Lattice Boltzmann model has been widely used as a quite convenient tool. Moreover, the Lattice Bol...
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Chapter and Conference Paper
Referential kNN Regression for Financial Time Series Forecasting
In this paper we propose a new multivariate regression approach for financial time series forecasting based on knowledge shared from referential nearest neighbors. Our approach defines a two-tier architecture....
