Abstract— Distributed stream processing systems offer a highly scalable and dynamically configurable platform for time-critical applications ranging from real-time, exploratory ...
Lisa Amini, Navendu Jain, Anshul Sehgal, Jeremy Si...
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical ...
In contextual advertising, estimating the number of impressions of an ad is critical in planning and budgeting advertising campaigns. However, producing this forecast, even within...
Xuerui Wang, Andrei Z. Broder, Marcus Fontoura, Va...
—In this paper, we present a general technique based on Bayesian inference to locate mobiles in cellular networks. We study the problem of localizing users in a cellular network ...
One important problem in machine learning is how to extract knowledge from prior experience, then transfer and apply this knowledge in new learning tasks. To address this problem, ...