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This paper introduces a classification algorithm called phHyperCuts. Like the previously best known algorithm, HiCuts, HyperCuts is based on a decision tree structure. Unlike HiCuts, however, in which each node in the decision tree represents a hyperplane, each node in the HyperCuts decision tree represents a <i>k</i>--dimensional hypercube. Using this(More)
Machine-Learning tasks are becoming pervasive in a broad range of domains, and in a broad range of systems (from embedded systems to data centers). At the same time, a small set of machine-learning algorithms (especially Convolutional and Deep Neural Networks, i.e., CNNs and DNNs) are proving to be state-of-the-art across many applications. As architectures(More)
Many companies are deploying services, either for consumers or industry, which are largely based on machine-learning algorithms for sophisticated processing of large amounts of data. The state-of-the-art and most popular such machine-learning algorithms are Convolutional and Deep Neural Networks (CNNs and DNNs), which are known to be both computationally(More)
In flowering plants, tapetum degeneration is proposed to be triggered by a programmed cell death (PCD) process during late stages of pollen development; the PCD is thought to provide cellular contents supporting pollen wall formation and to allow the subsequent pollen release. However, the molecular basis regulating tapetum PCD in plants remains poorly(More)
The use of peer-to-peer (P2P) applications is growing dramaticaliy, particularly for sharing large video/audio files and software. In this paper, we analyze P2P traffic by measuring flow-level information collected at multiple border routers across a large ISP network, and report our investigation of three popular P2P systems -- FastTrack, Gnutella, and(More)
Knowing the distribution of the sizes of traffic flows passing through a network link helps a network operator to characterize network resource usage, infer traffic demands, detect traffic anomalies, and accommodate new traffic demands through better traffic engineering. Previous work on estimating the flow size distribution has been focused on making(More)
The k-truss is a type of cohesive subgraphs proposed recently for the study of networks. While the problem of computing most cohesive subgraphs is NP-hard, there exists a polynomial time algorithm for computing k-truss. Compared with k-core which is also efficient to compute, k-truss represents the " core " of a k-core that keeps the key information of,(More)
—Cloud Computing has great potential of providing robust computational power to the society at reduced cost. It enables customers with limited computational resources to outsource their large computation workloads to the cloud, and economically enjoy the massive computational power, bandwidth, storage, and even appropriate software that can be shared in a(More)
Entropy has recently gained considerable significance as an important metric for network measurement. Previous research has shown its utility in clustering traffic and detecting traffic anomalies. While measuring the entropy of the traffic observed at a single point has already been studied, an interesting open problem is to measure the entropy of the(More)
CONTEXT Many men with inguinal hernia have minimal symptoms. Whether deferring surgical repair is a safe and acceptable option has not been assessed. OBJECTIVE To compare pain and the physical component score (PCS) of the Short Form-36 Version 2 survey at 2 years in men with minimally symptomatic inguinal hernias treated with watchful waiting or surgical(More)