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This work develops a distributed optimization algorithm with guaranteed exact convergence for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy is shown to have a wider stability range and superior convergence performance than the EXTRA consensus strategy. The exact diffusion solution is also applicable to non-symmetric left-stochastic combination matrices,...
The stochastic dual coordinate-ascent (S-DCA) technique is a useful alternative to the traditional stochastic gradient-descent algorithm for solving large-scale optimization problems due to its scalability to large data sets and strong theoretical guarantees. However, the available S-DCA formulation is limited to finite sample sizes and relies on performing multiple passes over the same data. This...
Online social media such as Weibo generates copious and to-the-minute information about real-world events of all kinds. How to effectively and efficiently detect emergent events from massive tweet streams is now drawing attention from various sources of every interest. Despite the wealth of previous research work, bursty topic detection (or burst prediction) remains a huge challenge because of certain...
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