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The extreme volume and staggeringly increasing rate inevitably produce unprecedented pressure on any large scale video sharing and hosting systems. Among the efforts to mitigate this pressure, content-based video similarity search is becoming more and more important with the exponential growth of the data size. Though various approaches have been proposed to address this problem, they are mainly focusing...
Communication over doubly selective channels (both time and frequency selective) suffers from significant intercarrier interference (ICI). This problem is severe in underwater acoustic communications. In this paper, a new Partial Fractional Fourier (PFrFT) based orthogonal frequency division multiplex (OFDM) scenario is presented for dealing with such challenges. A band minimum mean square error (BMMSE)...
We tackle the problem of answering maximum probabilistic top-k tuple set queries. We use a sliding-window model on uncertain data streams and present an efficient algorithm for processing sliding-window queries on uncertain streams. In each sliding window, the algorithm selects the k tuples with the highest probabilities from sets of different numbers of the tuples with the highest scores. Then, the...
Mission-critical target detection imposes stringent performance requirements for wireless sensor networks, such as high detection probabilities and low false alarm rates. Data fusion has been shown as an effective technique for improving system detection performance by enabling efficient collaboration among sensors with limited sensing capability. Due to the high cost of network deployment, it is...
A major challenge for learning Bayesian networks is the complexity in searching the huge space of models and parameters. The computational cost is higher when the model topology is more flexible. In this paper, we propose the notion of dominance which can lead to strong pruning of the search space and significant reduction of learning complexity, and apply this notion to the generalized latent class...
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