82 research outputs found
On converse bounds for classical communication over quantum channels
We explore several new converse bounds for classical communication over
quantum channels in both the one-shot and asymptotic regimes. First, we show
that the Matthews-Wehner meta-converse bound for entanglement-assisted
classical communication can be achieved by activated, no-signalling assisted
codes, suitably generalizing a result for classical channels. Second, we derive
a new efficiently computable meta-converse on the amount of classical
information unassisted codes can transmit over a single use of a quantum
channel. As applications, we provide a finite resource analysis of classical
communication over quantum erasure channels, including the second-order and
moderate deviation asymptotics. Third, we explore the asymptotic analogue of
our new meta-converse, the -information of the channel. We show that
its regularization is an upper bound on the classical capacity, which is
generally tighter than the entanglement-assisted capacity and other known
efficiently computable strong converse bounds. For covariant channels we show
that the -information is a strong converse bound.Comment: v3: published version; v2: 18 pages, presentation and results
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Performance of summarization for 24 diseases.
<p>Performance of summarization for 24 diseases.</p
Relationship between ROUGE-1 and the trade-off parameter ω.
<p>Relationship between ROUGE-1 and the trade-off parameter ω.</p
Comparison of summarization performance on ROUGE-1.
<p>Comparison of summarization performance on ROUGE-1.</p
An example of relation and sentence retrieval.
<p>An example of relation and sentence retrieval.</p
The impact of relation expansion, noise filtering and redundant removal.
<p>The impact of relation expansion, noise filtering and redundant removal.</p
Semantic relation network for “Angina Pectoris” after relation retrieval.
<p>Semantic relation network for “Angina Pectoris” after relation retrieval.</p
Relationship between ROUGE-1 and the trade-off parameter
<p>Relationship between ROUGE-1 and the trade-off parameter </p
A Single Kernel-Based Approach to Extract Drug-Drug Interactions from Biomedical Literature
<div><p>When one drug influences the level or activity of another drug this is known as a drug-drug interaction (DDI). Knowledge of such interactions is crucial for patient safety. However, the volume and content of published biomedical literature on drug interactions is expanding rapidly, making it increasingly difficult for DDIs database curators to detect and collate DDIs information manually. In this paper, we propose a single kernel-based approach to extract DDIs from biomedical literature. This novel kernel-based approach can effectively make full use of syntactic structural information of the dependency graph. In particular, our approach can efficiently represent both single subgraph topological information and the relation of two subgraphs in the dependency graph. Experimental evaluations showed that our single kernel-based approach can achieve state-of-the-art performance on the publicly available DDI corpus without exploiting multiple kernels or additional domain resources.</p> </div
The core relation set for “Angina Pectoris”.
<p>The core relation set for “Angina Pectoris”.</p
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