Learning from noisy data is a challenging and reality issue for real-world data mining applications. Common practices include data cleansing, error detection and classifier ensemb...
Yan Zhang, Xingquan Zhu, Xindong Wu, Jeffrey P. Bo...
One of the major drawbacks in block-based discrete cosine transform (BDCT) is the blocking artifacts at low bit rates. In this paper, an adaptive deblocking algorithm based on Mar...
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
The immanent existence of system latency greatly affects the control behavior of a closed-loop system. In order to reduce the influence induced by latency, this paper proposes a ...
Telemedicine is a mean of facilitating the distribution of human resources and professional competences. It can speed up diagnosis and therapeutic care delivery and allow peripher...
In this paper we present a prediction process of the Stock Exchange of Thailand index using adaptive evolution strategies. The prediction process does not require the knowledge of...
Lotos is the ISO formal specification language for describing and verifying concurrent and distributed systems. The simulation or execution of complex Lotos specifications is, h...