Search For:

Displaying 1-50 out of 51 total
Function Finding and Constants Creation Method in Evolutionary Algorithm Based on Overlapped Gene Expression
Found in: International Conference on Natural Computation
By Jing Peng, Chang-jie Tang, Dong-qing Yang, Shao-jie Qiao, Jing Zhang
Issue Date:August 2007
pp. 18-22
Evolutionary algorithm based on overlapped gene expression (EAOGE) is a new technology of evolutionary algorithm which is inspired by the overlap gene expression in biological research. Different from existing works, EAOGE suggests a new expression structu...
 
Framework for Intrusion Tolerant Certification Authority System Evaluation
Found in: Reliable Distributed Systems, IEEE Symposium on
By Jingqiang Lin, Jiwu Jing, Peng Liu
Issue Date:October 2007
pp. 231-241
Various intrusion tolerant certification authority (CA) systems have been recently proposed to provide attack resistant certificate update/query services. However, it is difficult to compare them against each other directly due to diversity in system organ...
 
IEEE Workshop Learning in Computer Vision and Pattern Recognition
Found in: Computer Vision and Pattern Recognition Workshop
By Bir Bhanu, Jing Peng, Bruce Draper
Issue Date:July 2004
pp. 92
No summary available.
   
CLOUD SHREDDER: Removing the Laptop On-road Data Disclosure Threat in the Cloud Computing Era
Found in: IEEE TrustCom/IEEE ICESS/FCST, International Joint Conference of
By Nan Zhang,Jiwu Jing,Peng Liu
Issue Date:November 2011
pp. 1592-1599
Data Disclosure due to laptop loss, especially in travel, is a top threat to businesses, governments, and non-profit organizations. An effective protection against this threat should guarantee the data confidentiality, even if the adversary has physically ...
 
CCA-Secure Type-based Proxy Re-encryption with Invisible Proxy
Found in: Computer and Information Technology, International Conference on
By Xiaoqi Jia, Jun Shao, Jiwu Jing, Peng Liu
Issue Date:July 2010
pp. 1299-1305
Proxy re-encryption is a useful cryptographic primitive, which allows a proxy to transform a ciphertext for Alice to another ciphertext of the same plaintext for Bob. Type-based proxy re-encryption is a specific kind of proxy re-encryption, where the proxy...
 
A Concept Similarity Based Text Classification Algorithm
Found in: Fuzzy Systems and Knowledge Discovery, Fourth International Conference on
By Jing Peng, Dong-qing Yang, Shi-Wei Tang, Jun Gao, Peng-yi Zhang, Yan Fu
Issue Date:August 2007
pp. 535-539
Text classification is an important task of data mining. Existing algorithms, which based on vector space models, does not considered concept similarities among words, so the accuracy of traditional text classification cannot guarantee. To solve the proble...
 
Learning Optimal Filter Representation for Texture Classification
Found in: Pattern Recognition, International Conference on
By Peng Zhang, Jing Peng, Bill Buckles
Issue Date:August 2006
pp. 1138-1141
Crucial to texture classification are texture features and classifiers that operate on the features. There are several approaches to computing texture features. Of particular interest is multichannel filtering because of its simplicity. Multichannel filter...
 
Discriminant Analysis: A Least Squares Approximation View
Found in: Computer Vision and Pattern Recognition Workshop
By Peng Zhang, Jing Peng, Nobert Riedel
Issue Date:June 2005
pp. 46
<p>Linear discriminant analysis (LDA) is a very important approach to selecting features in classification such as facial recognition. However it suffers from the small sample size (SSS) problem where LDA cannot be solved numerically. The SSS problem...
 
SVM vs Regularized Least Squares Classification
Found in: Pattern Recognition, International Conference on
By Peng Zhang, Jing Peng
Issue Date:August 2004
pp. 176-179
Support vector machines (SVMs) and regularized least squares (RLS) are two recent promising techniques for classification. SVMs implement the structure risk minimization principle and use the kernel trick to extend it to the non-linear case. On the other h...
 
Efficient Regularized Least Squares Classification
Found in: Computer Vision and Pattern Recognition Workshop
By Peng Zhang, Jing Peng
Issue Date:July 2004
pp. 98
Kernel-based regularized least squares (RLS) algorithms are a promising technique for classification. RLS minimizes a regularized functional directly in a reproducing kernel Hilbert space defined by a kernel. In contrast, support vector machines (SVMs) imp...
 
Dimensionality Reduction Using Kernel Pooled Local Discriminant Information
Found in: Data Mining, IEEE International Conference on
By Peng Zhang, Jing Peng, Carlotta Domeniconi
Issue Date:November 2003
pp. 701
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and compare it against several competing techniques: generalized Fisher discriminant ...
 
Kernel Pooled Local Subspaces for Classification
Found in: Computer Vision and Pattern Recognition Workshop
By Peng Zhang, Jing Peng, Carlotta Domeniconi
Issue Date:June 2003
pp. 63
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and compare it against several competing techniques: Principal Component Analysis (PC...
 
An Empirical Study of a Chinese Online Social Network--Renren
Found in: Computer
By Jianwei Niu,Jing Peng,Lei Shu,Chao Tong,Wanjiun Liao
Issue Date:September 2013
pp. 78-84
Deeper knowledge of social networks' structure and temporal evolution enhances data mining for both research and education purposes. An empirical analysis of a Chinese social network, Renren, shows that it follows an exponentially truncated power law in de...
 
Privacy Preserving for Continuous Query in Location Based Services
Found in: 2012 IEEE 18th International Conference on Parallel and Distributed Systems (ICPADS)
By Yong Wang,Long-ping He,Jing Peng,Ting-ting Zhang,Hong-zong Li
Issue Date:December 2012
pp. 213-220
Location-based services (LBSs) have become a popular and important way to provide real-time information and guidance. The abuse of mobile users' location data, which may violate their sensitive and private personal information, is one of the major challeng...
 
Efficient Privacy Preserving Matchmaking for Mobile Social Networking against Malicious Users
Found in: 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
By Yong Wang,Ting-Ting Zhang,Hong-Zong Li,Long-Ping He,Jing Peng
Issue Date:June 2012
pp. 609-615
Making friends with some common attributes is one of the most popular applications in the mobile social networking (MSN). However, how to preserve the users' privacy while matchmaking has been considered as the key security issue for such applications. In ...
 
Application Study on Collaborative Mobile Electronic Commerce
Found in: International Conference on E-Business and E-Government
By Wang Jing,He Peng
Issue Date:May 2010
pp. 18-21
As the mobile electronic commerce constantly develops in our country, there emerge problems like the imperfect payment system, poor transaction security and incomplete credit system, etc. Collaborative mobile electronic commerce, proposed in this paper, ha...
 
Subdividing Hexagon-Clustered Wireless Sensor Networks for Power-Efficiency
Found in: Communications and Mobile Computing, International Conference on
By Dajin Wang, Li Xu, Jing Peng, Stefan Robila
Issue Date:January 2009
pp. 454-458
Hexagons are an ideal shape for clustering sensor networks, because clustered areas can be seamlessly divided by the hexagons. In addition, hexagons are the largest regular polygon (in terms of the number of sides) that has this property. In this paper, we...
 
PartSpan: Parallel Sequence Mining of Trajectory Patterns
Found in: Fuzzy Systems and Knowledge Discovery, Fourth International Conference on
By Shaojie Qiao, Changjie Tang, Shucheng Dai, Mingfang Zhu, Jing Peng, Hongjun Li, Yungchang Ku
Issue Date:October 2008
pp. 363-367
The trajectory pattern mining problem has recently attracted increasing attention. This paper precisely addresses the parallel mining problem of trajectory patterns as well as the newly proposed concepts with regard to trajectory pattern mining. An efficie...
 
Efficient k-Closest-Pair Range-Queries in Spatial Databases
Found in: Web-Age Information Management, International Conference on
By Shaojie Qiao, Changjie Tang, Jing Peng, Hongjun Li, Shengqiao Ni
Issue Date:July 2008
pp. 99-104
In order to efficiently retrieve the k closest pairs between two spatial data sets in a specified space, such as in GIS and CAD applications, we propose a novel algorithm to handle the k-closest-pair range-query problem by progressively augmenting the quer...
 
Weighted Additive Criterion for Linear Dimension Reduction
Found in: Data Mining, IEEE International Conference on
By Jing Peng, Stefan Robila
Issue Date:October 2007
pp. 619-624
Linear discriminant analysis (LDA) for dimension reduction has been applied to a wide variety of face recognition tasks. However, it has two major problems. First, it suffers from the small sample size problem when dimensionality is greater than the sample...
 
An Ensemble Approach to Robust Biometrics Fusion
Found in: Computer Vision and Pattern Recognition Workshop
By Costin Barbu, Raja Iqbal, Jing Peng
Issue Date:June 2006
pp. 56
A clever information fusion algorithm is a key component in designing a robust multimodal biometrics algorithm. We present a novel information fusion approach that can be a very useful tool for multimodal biometrics learning. The proposed technique is a mu...
 
Classifier Fusion Using Shared Sampling Distribution for Boosting
Found in: Data Mining, IEEE International Conference on
By Costin Barbu, Raja Iqbal, Jing Peng
Issue Date:November 2005
pp. 34-41
We present a new framework for classifier fusion that uses a shared sampling distribution for obtaining a weighted classifier ensemble. The weight update process is self regularizing as subsequent classifiers trained on the disjoint views rectify the bias ...
 
Learning through Changes: An Empirical Study of Dynamic Behaviors of Probability Estimation Trees
Found in: Data Mining, IEEE International Conference on
By Kun Zhang, Zujia Xu, Jing Peng, Bill Buckles
Issue Date:November 2005
pp. 817-820
In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probability estimation tree algorithms over eighteen binary classification problems. ...
 
Distributed-Log-based Scheme for IP Traceback
Found in: Computer and Information Technology, International Conference on
By Yi-Nan Jing, Peng Tu, Xue-Ping Wang, Gen-Du Zhang
Issue Date:September 2005
pp. 711-715
<p>IP traceback is one of the most effective techniques to defeat the denial-of-service attacks and distributed denial-of-service attacks. And based on previous research, available probabilistic packet marking (PPM) schemes have more advantages than ...
 
The Role of Reactivity in Multiagent Learning
Found in: Autonomous Agents and Multiagent Systems, International Joint Conference on
By Bikramjit Banerjee, Jing Peng
Issue Date:July 2004
pp. 538-545
In this paper we take a closer look at a recently proposed classification scheme for multiagent learning algorithms. Based on this scheme an exploitation mechanism (we call it the Exploiter) was developed that could beat various Policy Hill Climbers (PHC) ...
 
Adaptive Quasiconformal Kernel Nearest Neighbor Classification
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Jing Peng, Douglas R. Heisterkamp, H.K. Dai
Issue Date:May 2004
pp. 656-661
<p><b>Abstract</b>—Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to the curse-of-dimensionality. Severe bias can be introduced under these ...
 
Adaptive Kernel Metric Nearest Neighbor Classification
Found in: Pattern Recognition, International Conference on
By Jing Peng, Douglas R. Heisterkamp, H. K. Dai
Issue Date:August 2002
pp. 30033
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to the curse-of-dimensionality. Severe bias can be introduced under these conditions when using the nearest nei...
 
Adaptive Quasiconformal Kernel Metric for Image Retrieval
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Douglas R. Heisterkamp, Jing Peng, H. K. Dai
Issue Date:December 2001
pp. 388
This paper presents a new approach to ranking relevant images for retrieval. Distance in the feature space associated with a kernel is used to rank relevant images. An adaptive quasiconformal mapping based on relevance feedback is used to generate successi...
 
LDA/SVM Driven Nearest Neighbor Classification
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Jing Peng, Douglas R. Heisterkamp, H. K. Dai
Issue Date:December 2001
pp. 58
Nearest neighbor classification relies on the assumption that class conditional probabilities are locally constant. This assumption becomes false in high dimensions with finite samples due to the curse of dimensionality. The nearest neighbor rule introduce...
 
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Found in: Pattern Recognition, International Conference on
By Douglas R. Heisterkamp, Jing Peng, H.K. Dai
Issue Date:September 2000
pp. 4250
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes less attractive in situations where all the input variables have the same local...
 
Adaptive Metric nearest Neighbor Classification
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Carlotta Domeniconi, Dimitrios Gunopulos, Jing Peng
Issue Date:June 2000
pp. 1517
Nearest neighbor, classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with finite samples due to the curse of dimensionality. Severe bias can be introduced under these conditions when ...
 
Adaptive Target Recognition
Found in: Computer Vision Beyond the Visible Spectrum, IEEE Workshop on
By Bir Bhanu, Yingqiang Lin, Grinnell Jones, Jing Peng
Issue Date:June 1999
pp. 71
Target recognition is a multi-level process requiring a sequence of algorithms at low, intermediate and high levels. Generally, such systems are open loop with no feedback between levels and assuring their performance at the given Probability of Correct Id...
 
Closed-Loop Object Recognition Using Reinforcement Learning
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Jing Peng, Bir Bhanu
Issue Date:February 1998
pp. 139-154
<p><b>Abstract</b>—Current computer vision systems whose basic methodology is open-loop or <it>filter</it> type typically use image segmentation followed by object recognition algorithms. These systems are not robust for most ...
 
Closed-Loop Object Recognition Using Reinforcement Learning
Found in: Computer Vision and Pattern Recognition, IEEE Computer Society Conference on
By Jing Peng, Bir Bhanu
Issue Date:June 1996
pp. 538
Current computer vision systems whose basic methodology is open-loop or filter type typically use image segmentation followed by object recognition algorithms. These systems are not robust for most real-world applications. In contrast, the system presented...
 
Combining the advice of experts with randomized boosting for robust pattern recognition
Found in: 2013 IEEE Applied Imagery Pattern Recognition Workshop: Sensing for Control and Augmentation (AIPR 2013)
By Jing Peng,Guna Seetharaman
Issue Date:October 2013
pp. 1-7
We have developed an algorithm, called ShareBoost, for combining mulitple classifiers from multiple information sources. The algorithm offer a number of advantages, such as increased confidence in decision-making, resulting from combined complementary data...
   
Graph-Based Iterative Hybrid Feature Selection
Found in: Data Mining, IEEE International Conference on
By ErHeng Zhong, Sihong Xie, Wei Fan, Jiangtao Ren, Jing Peng, Kun Zhang
Issue Date:December 2008
pp. 1133-1138
When the number of labeled examples is limited, traditional supervised feature selection techniques often fail due to sample selection bias or unrepresentative sample problem. To solve this, semi-supervised feature selection techniques exploit the statisti...
 
Locally Adaptive Metric Nearest-Neighbor Classification
Found in: IEEE Transactions on Pattern Analysis and Machine Intelligence
By Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos
Issue Date:September 2002
pp. 1281-1285
<p><b>Abstract</b>—Nearest-neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with finite samples due to the curse of dimensionality. Severe bias can be int...
 
A NEW CONTENT-BASED IMAGE RETRIEVAL SYSTEM USING HANG GESTURE AND RELEVANGE FEEDBACK
Found in: Multimedia and Expo, IEEE International Conference on
By ByongChul Ko, Jing Peng, Hyeran Byun
Issue Date:August 2001
pp. 98
Current research on Content-Based Image Retrieval (CBIR) is centered on designing efficient query schemes in order to provide a user with effective mechanisms for image database search. Among representative CBIR query schemes, query-by-sketch has been one ...
 
Local Reinforcement Learning for Object Recognition
Found in: Pattern Recognition, International Conference on
By Jing Peng, Bir Bhanu
Issue Date:August 1998
pp. 272
No summary available.
 
A Random Walk Model for Item Recommendation in Social Tagging Systems
Found in: ACM Transactions on Management Information Systems (TMIS)
By Ahmed Abbasi, Daniel D. Zeng, Jing Peng, Xiaolong Zheng, Zhu Zhang
Issue Date:August 2013
pp. 1-24
Social tagging, as a novel approach to information organization and discovery, has been widely adopted in many Web 2.0 applications. Tags contributed by users to annotate a variety of Web resources or items provide a new type of information that can be exp...
     
Exploiting fisher and fukunaga-koontz transforms in chernoff dimensionality reduction
Found in: ACM Transactions on Knowledge Discovery from Data (TKDD)
By Aparna Varde, Guna Seetharaman, Jing Peng, Wei Fan
Issue Date:July 2013
pp. 1-25
Knowledge discovery from big data demands effective representation of data. However, big data are often characterized by high dimensionality, which makes knowledge discovery more difficult. Many techniques for dimensionality reudction have been proposed, i...
     
Cross-layer comprehensive intrusion harm analysis for production workload server systems
Found in: Proceedings of the 26th Annual Computer Security Applications Conference (ACSAC '10)
By Jiwu Jing, Peng Liu, Shengzhi Zhang, Xiaoqi Jia
Issue Date:December 2010
pp. 297-306
Analyzing the (harm of) intrusion to enterprise servers is an onerous and error-prone work. Though dynamic taint tracking enables automatic fine-grained intrusion harm analysis for enterprise servers, the significant runtime overhead introduced is generall...
     
Incorporating terminology evolution for query translation in text retrieval with association rules
Found in: Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM '10)
By Amal C. Kaluarachchi, Anna Feldman, Aparna S. Varde, Gerhard Weikum, Jing Peng, Srikanta Bedathur
Issue Date:October 2010
pp. 1789-1792
Time-stamped documents such as newswire articles, blog posts and other web-pages are often archived online. When these archives cover long spans of time, the terminology within them could undergo significant changes. Hence, when users pose queries pertaini...
     
Collaborative filtering in social tagging systems based on joint item-tag recommendations
Found in: Proceedings of the 19th ACM international conference on Information and knowledge management (CIKM '10)
By Daniel Dajun Zeng, Fei-yue Wang, Huimin Zhao, Jing Peng
Issue Date:October 2010
pp. 809-818
Tapping into the wisdom of the crowd, social tagging can be considered an alternative mechanism - as opposed to Web search - for organizing and discovering information on the Web. Effective tag-based recommendation of information items, such as Web resourc...
     
Cross domain distribution adaptation via kernel mapping
Found in: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '09)
By Deepak Turaga, Erheng Zhong, Jiangtao Ren, Jing Peng, Kun Zhang, Olivier Verscheure, Wei Fan
Issue Date:June 2009
pp. 1-24
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the assumption made by existing approaches, that the marginal and conditional pr...
     
Latent space domain transfer between high dimensional overlapping distributions
Found in: Proceedings of the 18th international conference on World wide web (WWW '09)
By Jiangtao Ren, Jing Peng, Olivier Verscheure, Sihong Xie, Wei Fan
Issue Date:April 2009
pp. 66-66
Transferring knowledge from one domain to another is challenging due to a number of reasons. Since both conditional and marginal distribution of the training data and test data are non-identical, model trained in one domain, when directly applied to a diff...
     
Using virtual machines to do cross-layer damage assessment
Found in: Proceedings of the 1st ACM workshop on Virtual machine security (VMSec '08)
By Jiwu Jing, Peng Liu, Shengzhi Zhang, Xiaoqi Jia
Issue Date:October 2008
pp. 53-62
In this paper, we present an approach that uses virtual machines to do ``out-of-the-box'' cross-layer damage assessment, an indispensable part of security/risk management. To resolve the conflict between fine-grained damage assessment and the response time...
     
RVσ(t): a unifying approach to performance and convergence in online multiagent learning
Found in: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (AAMAS '06)
By Bikramjit Banerjee, Jing Peng
Issue Date:May 2006
pp. 798-800
We present a new multiagent learning algorithm (RVσ(t) that can guarantee both no-regret performance (all games) and policy convergence (some games of arbitrary size). Unlike its predecessor ReDVaLeR, it (1) does not need to distinguish whether its o...
     
Efficient learning of multi-step best response
Found in: Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems (AAMAS '05)
By Bikramjit Banerjee, Jing Peng
Issue Date:July 2005
pp. 60-66
We provide a uniform framework for learning against a recent history adversary in arbitrary repeated bimatrix games, by modeling such an agent as a Markov Decision Process. We focus on learning an optimal non-stationary policy in such an MDP over a finite ...
     
Segmentation in Chinese natural language understanding using a massively parallel approach (abstract)
Found in: Proceedings of the 1986 ACM fourteenth annual conference on Computer science (CSC '86)
By Hon Wai Chun, Jing Peng, Tangqui Li, Xiru Zhang
Issue Date:February 1986
pp. 442
A description of an advanced graphics interface design that provides the applications developer with a very high level graphics environment is presented. The object oriented design is shown to be appropriate to achieving device and implementation independe...
     
 1  2 Next >>