Advances in Knowledge Discovery and Data Mining
19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II
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25 Result(s)
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**n Hua Zhou
Artificial Intelligence
Data Mining and Knowledge Discovery
Information Storage and Retrieval
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Chapter and Conference Paper
Social Stream Classification with Emerging New Labels
As an important research topic with well-recognized practical values, classification of social streams has been identified with increasing popularity with social data, such as the tweet stream generated by Twi...
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Chapter and Conference Paper
Multi-View Matrix Completion for Clustering with Side Information
In many clustering applications, real world data are often collected from multiple sources or with features from multiple channels. Thus, multi-view clustering has attracted much attention during the past few ...
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Chapter and Conference Paper
A Lower Bound Analysis of Population-Based Evolutionary Algorithms for Pseudo-Boolean Functions
Evolutionary algorithms (EAs) are population-based general-purpose optimization algorithms, and have been successfully applied in real-world optimization tasks. However, previous theoretical studies often empl...
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Chapter and Conference Paper
Facial Age Estimation by Total Ordering Preserving Projection
Facial age estimation is one of the unsolved challenging issues in automatic face perception. Previous studies usually formulated it as a classification problem, where each age is regarded as a class, or a reg...
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Book and Conference Proceedings
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Book and Conference Proceedings
Advances in Knowledge Discovery and Data Mining
19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I
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Book and Conference Proceedings
Trends and Applications in Knowledge Discovery and Data Mining
PAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH, Ho Chi Minh City, Vietnam, May 19-21, 2015. Revised Selected Papers
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Chapter and Conference Paper
Text Relevance Analysis Method over Large-Scale High-Dimensional Text Data Processing
As the amount of digital information is exploding in social, industry and scientific areas, MapReduce is a distributed computation framework, which has become widely adopted for analytics on large-scale data. ...
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Book and Conference Proceedings
Advances in Knowledge Discovery and Data Mining
18th Pacific-Asia Conference, PAKDD 2014, Tainan, Taiwan, May 13-16, 2014. Proceedings, Part I
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Book and Conference Proceedings
Advances in Knowledge Discovery and Data Mining
18th Pacific-Asia Conference, PAKDD 2014, Tainan, Taiwan, May 13-16, 2014. Proceedings, Part II
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Book and Conference Proceedings
Trends and Applications in Knowledge Discovery and Data Mining
PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers
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Chapter and Conference Paper
A PWF Smoothing Algorithm for K-Sensitive Stream Mining Technologies over Sliding Windows
The development of Streaming Mining technologies as a hotspot entered the limelight, which is more effectively to avoid big data and distributed streams mining problems. Especially for the IoT and Ubiquitous Comp...
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Article
Exploiting unlabeled data to enhance ensemble diversity
Ensemble learning learns from the training data by generating an ensemble of multiple base learners. It is well-known that to construct a good ensemble with strong generalization ability, the base learners are...
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Chapter and Conference Paper
Stability of a Predator-Prey Model with Modified Holling-Type II Functional Response
A predator-prey model with modified Holling-Type II functional response under Neumann boundary condition is proposed. We show that under some conditions the cross-diffusion can induce the Turing instability of...
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Chapter and Conference Paper
Using Multiple Objective Functions in the Dynamic Model of Metabolic Networks of Escherichia coli
Different objective functions in the dynamic model can explore the diverse properties of the solution space, and a wide variety of capabilities of an organism. In that way, when there is a fact that several co...
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Chapter and Conference Paper
Diversity Regularized Ensemble Pruning
Diversity among individual classifiers is recognized to play a key role in ensemble, however, few theoretical properties are known for classification. In this paper, by focusing on the popular ensemble pruning...
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Chapter and Conference Paper
Towards Cost-Sensitive Learning for Real-World Applications
Many research work in cost-sensitive learning focused on binary class problems and assumed that the costs are precise. But real-world applications often have multiple classes and the costs cannot be obtained p...
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Chapter and Conference Paper
On Detecting Clustered Anomalies Using SCiForest
Detecting local clustered anomalies is an intricate problem for many existing anomaly detection methods. Distance-based and density-based methods are inherently restricted by their basic assumptions—anomalies ...
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Chapter and Conference Paper
When does Co-training Work in Real Data?
Co-training, a paradigm of semi-supervised learning, may alleviate effectively the data scarcity problem (i.e., the lack of labeled examples) in supervised learning. The standard two-view co-training requires ...
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Chapter and Conference Paper
Budget Semi-supervised Learning
In this paper we propose to study budget semi-supervised learning, i.e., semi-supervised learning with a resource budget, such as a limited memory insufficient to accommodate and/or process all available unlabele...
