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Item-based Collaborative Filtering (CF) algorithms have been designed to deal with the scalability problems associated with traditional user-based CF approaches without sacrificing recommendation or prediction accuracy. Item-based algorithms avoid the bottleneck in computing user-user correlations by first considering the relationships among items and(More)
We present Dionysus, a system for fast, consistent network updates in software-defined networks. Dionysus encodes as a graph the consistency-related dependencies among updates at individual switches, and it then dynamically schedules these updates based on runtime differences in the update speeds of different switches. This dynamic scheduling is the key to(More)
Recently, there has been considerable interest in attribute based access control (ABAC) to overcome the limitations of the dominant access control models (i.e, discretionary-DAC, mandatory-MAC and role based-RBAC) while unifying their advantages. Although some proposals for ABAC have been published, and even implemented and standardized, there is no(More)
— SpiNNaker is a novel chip – based on the ARM processor – which is designed to support large scale spiking neural networks simulations. In this paper we describe some of the features that permit SpiNNaker chips to be connected together to form scalable massively-parallel systems. Our eventual goal is to be able to simulate neural networks consisting of 10(More)
The basal ganglia are subcortical nuclei that control voluntary actions, and they are affected by a number of debilitating neurological disorders. The prevailing model of basal ganglia function proposes that two orthogonal projection circuits originating from distinct populations of spiny projection neurons (SPNs) in the striatum--the so-called direct and(More)
The ability to learn new skills and perfect them with practice applies not only to physical skills but also to abstract skills, like motor planning or neuroprosthetic actions. Although plasticity in corticostriatal circuits has been implicated in learning physical skills, it remains unclear if similar circuits or processes are required for abstract skill(More)
Information networks are ubiquitous in many applications and analysis on such networks has attracted significant attention in the academic communities. One of the most important aspects of information network analysis is to measure similarity between nodes in a network. SimRank is a simple and influential measure of this kind, based on a solid theoretical(More)
Learning new action sequences subserves a plethora of different abilities such as escaping a predator, playing the piano, or producing fluent speech. Proper initiation and termination of each action sequence is critical for the organization of behaviour, and is compromised in nigrostriatal disorders like Parkinson's and Huntington's diseases. Using a(More)
Targeted capture combined with massively parallel exome sequencing is a promising approach to identify genetic variants implicated in human traits. We report exome sequencing of 200 individuals from Denmark with targeted capture of 18,654 coding genes and sequence coverage of each individual exome at an average depth of 12-fold. On average, about 95% of the(More)
Chunking allows the brain to efficiently organize memories and actions. Although basal ganglia circuits have been implicated in action chunking, little is known about how individual elements are concatenated into a behavioral sequence at the neural level. Using a task in which mice learned rapid action sequences, we uncovered neuronal activity encoding(More)