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Localization from mere connectivity
TLDR
An algorithm that uses connectivity information who is within communications range of whom to derive the locations of the nodes in the network is presented, based on multidimensional scaling, a data analysis technique that takes O(n3) time for a network of n nodes.
HMDB: the Human Metabolome Database
TLDR
The Human Metabolome Database is designed to address the broad needs of biochemists, clinical chemists, physicians, medical geneticists, nutritionists and members of the metabolomics community.
Localization from connectivity in sensor networks
TLDR
Two methods that use connectivity information - who is within communications range of whom - to derive the locations of nodes in a network are presented and it is shown that the methods achieve more accurate solutions than previous methods, especially when there are few anchor nodes.
PGA: Using Graphs to Express and Automatically Reconcile Network Policies
TLDR
This work first develops a high-level Policy Graph Abstraction (PGA) that allows network policies to be expressed simply and independently, and leverage the graph structure to detect and resolve policy conflicts efficiently, and also models and composes service chaining policies.
Multivariate Time Series Imputation with Generative Adversarial Networks
TLDR
Experiments show that the proposed model outperformed the baselines in terms of accuracy of imputation, and a simple model on the imputed data can achieve state-of-the-art results on the prediction tasks, demonstrating the benefits of the model in downstream applications.
Interpreting BLEU/NIST Scores: How Much Improvement do We Need to Have a Better System?
TLDR
A novel method of calculating the confidence intervals for BLEU/NIST scores using bootstrapping is reported, which can determine whether two MT systems are significantly different from each other.
On Multiplicative Integration with Recurrent Neural Networks
TLDR
This work introduces a general and simple structural design called Multiplicative Integration, which changes the way in which information from difference sources flows and is integrated in the computational building block of an RNN, while introducing almost no extra parameters.
Adaptive output control of nonlinear systems with uncertain dead-zone nonlinearity
TLDR
A new scheme to design adaptive controllers for uncertain systems preceded by unknown dead-zone nonlinearity is presented and it is shown that the proposed controller not only can guarantee stability, but also transient performance.
SRBench: A Streaming RDF/SPARQL Benchmark
TLDR
SRBench is introduced, a general-purpose benchmark primarily designed for streaming RDF/SPARQL engines, completely based on real-world data sets from the Linked Open Data cloud, which defines a concise, yet comprehensive set of queries that cover the major aspects of strRS processing.
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