Vatsal Shah

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Stochastic gradient descent (SGD) is the method of choice for large-scale machine learning problems, by virtue of its light complexity per iteration. However, it lags behind its non-stochastic counterparts with respect to the convergence rate, due to high variance introduced by the stochastic updates. The popular Stochastic Variance-Reduced Gradient (Svrg)(More)
Network traffic anomaly detection is now considered a surer approach to early detection of malware than signature-based approaches and is best accomplished with traffic data collected from multiple locations. Existing open-source tools are primarily signature-based, or do not facilitate integration of traffic data from multiple locations for real-time(More)
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