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In recent years, Dynamic Adaptive Streaming over HTTP (DASH) has gained momentum as an effective solution for delivering videos on the Internet. This trend is further driven by the deployment of existing HTTP cache infrastructures in DASH systems to reduce the traffic load as well as to serve clients better. However, deploying conventional cache servers in DASH systems still suffers from low cache...
In this paper, we develop a novel incremental learning scheme for reinforcement learning (RL) in dynamic environments, where the reward functions may change over time instead of being static. The proposed incremental learning scheme aims at automatically adjusting the optimal policy in order to adapt to the ever-changing environment. We evaluate the proposed scheme on a classical maze navigation problem...
The computational prediction of protein-protein interactions is currently an important issue in biology. In this paper, a K-local hyperplane distance nearest neighbor (HKNN) classifiers with symmetrical encoding scheme is proposed to predict protein-protein interactions. Moreover, a new sample encoding scheme, named symmetrical encoding scheme (SYES), for protein pair is developed by which a single...
During recent years, the quick development of computer techniques has witnessed the ever-increasing surveillance video data, which essentially pose great challenge on the data storage, management, analysis and even retrieval. Considering that most of the high volume of data is with no interest, we mainly investigate the problem of effectively and efficiently discovering segments-of-interest (SoI)...
In this paper, a finite-mixture-model learning bused sparse component analysis (SCA) algorithm is proposed. In this algorithm, a finite-mixture-model learning method is applied for estimating the mixing matrix for SCA. The main advantage of this method is the ability of selecting the number of sources and measuring reliability of the columns of the estimated mixing matrix. That is, it can give us...
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