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  • Influence
Detecting insider threats in a real corporate database of computer usage activity
This paper reports on methods and results of an applied research project by a team consisting of SAIC and four universities to develop, integrate, and evaluate new approaches to detect the weakExpand
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Net-Ray: Visualizing and Mining Billion-Scale Graphs
How can we visualize billion-scale graphs? How to spot outliers in such graphs quickly? Visualizing graphs is the most direct way of understanding them; however, billion-scale graphs are veryExpand
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Towards Semi-Supervised Learning for Deep Semantic Role Labeling
Neural models have shown several state-of-the-art performances on Semantic Role Labeling (SRL). However, the neural models require an immense amount of semantic-role corpora and are thus not wellExpand
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StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization
Traditional preneural approaches to single document summarization relied on modeling the intermediate structure of a document before generating the summary. In contrast, the current state of the artExpand
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Influence Propagation: Patterns, Model and a Case Study
When a free, catchy application shows up, how quickly will people notify their friends about it? Will the enthusiasm drop exponentially with time, or oscillate? What other patterns emerge?
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Fast anomaly detection despite the duplicates
Given a large cloud of multi-dimensional points, and an off-the shelf outlier detection method, why does it take a week to finish? After careful analysis, we discovered that duplicate points createExpand
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Semi-Supervised Learning on Meta Structure: Multi-Task Tagging and Parsing in Low-Resource Scenarios
Multi-view learning makes use of diverse models arising from multiple sources of input or different feature subsets for the same task. For example, a given natural language processing task canExpand
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Enforcing Constraints on Outputs with Unconstrained Inference
Increasingly, practitioners apply neural networks to complex problems in natural language processing (NLP), such as syntactic parsing, that have rich output structures. Many such applications Expand
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Fast Outlier Detection Despite the Duplicates
Given a large cloud of multi-dimensional points, and an off-theshelf outlier detection method, why does it take a week to finish? After careful analysis, we discovered that duplicate points createExpand
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Enforcing Output Constraints via SGD: A Step Towards Neural Lagrangian Relaxation
Structured prediction problems such as named entity recognition and parsing are crucial for automated knowledge base construction. Increasingly, researchers are exploring ways of improving them withExpand
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