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Both random Fourier features and the Nyström method have been successfully applied to efficient kernel learning. In this work, we investigate the fundamental difference between these two approaches, and how the difference could affect their generalization performances. Unlike approaches based on random Fourier features where the basis functions (i.e.,(More)
We present and study a distributed optimization algorithm by employing a stochas-tic dual coordinate ascent method. Stochastic dual coordinate ascent methods enjoy strong theoretical guarantees and often have better performances than stochas-tic gradient descent methods in optimizing regularized loss minimization problems. It still lacks of efforts in(More)
In this paper, we consider the problem of combining link and content analysis for community detection from networked data, such as paper citation networks and Word Wide Web. Most existing approaches combine link and content information by a <i>generative</i> model that generates both links and contents via a shared set of community memberships. These(More)
We study the online convex optimization problem, in which an online algorithm has to make repeated decisions with convex loss functions and hopes to achieve a small regret. We consider a natural restriction of this problem in which the loss functions have a small deviation, measured by the sum of the distances between every two consecutive loss functions ,(More)
Legumes, such as Medicago truncatula, form mutualistic symbiotic relationships with nitrogen-fixing rhizobial bacteria. This occurs within specialized root organs--nodules--that provide the conditions required for nitrogen fixation. A rhizobium-derived signalling molecule, Nod factor, is required to establish the symbiosis. Perception of Nod factor in the(More)
In this paper we propose efficient algorithms for solving constrained online convex optimization problems. Our motivation stems from the observation that most algorithms proposed for online convex optimization require a projection onto the convex set K from which the decisions are made. While the projection is straightforward for simple shapes (e.g.,(More)
Intracellular calcium transients during plant-pathogen interactions are necessary early events leading to local and systemic acquired resistance. Salicylic acid, a critical messenger, is also required for both of these responses, but whether and how salicylic acid level is regulated by Ca(2+) signalling during plant-pathogen interaction is unclear. Here we(More)
Most studies of online learning measure the performance of a learner by classification accuracy , which is inappropriate for applications where the data are unevenly distributed among different classes. We address this limitation by developing online learning algorithm for maximizing Area Under the ROC curve (AUC), a metric that is widely used for measuring(More)
Fruit ripening is a complicated development process affected by a variety of external and internal cues. It is well established that calcium treatment delays fruit ripening and senescence. However, the underlying molecular mechanisms remain unclear. Previous studies have shown that calcium/calmodulin-regulated SR/CAMTAs are important for modulation of(More)
Although a large body of work is devoted to finding communities in static social networks, only a few studies examined the dynamics of communities in evolving social networks. In this paper, we propose a dynamic stochastic block model for finding communities and their evolution in a dynamic social network. The proposed model captures the evolution of(More)