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Found 10 papers, 2 papers with code
Noise Contrastive Estimation-based Matching Framework for Low-Resource Security Attack Pattern Recognition
Tactics, Techniques and Procedures (TTPs) represent sophisticated attack patterns in the cybersecurity domain, described encyclopedically in textual knowledge bases.
Enabling hand gesture customization on wrist-worn devices
We present a framework for gesture customization requiring minimal examples from users, all without degrading the performance of existing gesture sets.
On the Feasibility of Predicting Questions being Forgotten in Stack Overflow
In this work, we study this managed forgetting task for Stack Overflow.
Spatiotemporal Tile-based Attention-guided LSTMs for Traffic Video Prediction
This extended abstract describes our solution for the Traffic4Cast Challenge 2019.
A Trio Neural Model for Dynamic Entity Relatedness Ranking
Measuring entity relatedness is a fundamental task for many natural language processing and information retrieval applications.
On the Predictability of non-CGM Diabetes Data for Personalized Recommendation
With continuous glucose monitoring (CGM), data-driven models on blood glucose prediction have been shown to be effective in related work.
Multiple Models for Recommending Temporal Aspects of Entities
Entity aspect recommendation is an emerging task in semantic search that helps users discover serendipitous and prominent information with respect to an entity, of which salience (e. g., popularity) is the most important factor in previous work.
A Comprehensive Low and High-level Feature Analysis for Early Rumor Detection on Twitter
Recent work have done a good job in modeling rumors and detecting them over microblog streams.
On Early-stage Debunking Rumors on Twitter: Leveraging the Wisdom of Weak Learners
Recently a lot of progress has been made in rumor modeling and rumor detection for micro-blogging streams.
Dual Space Gradient Descent for Online Learning
However, this approach still suffers from a serious shortcoming as it needs to use a high dimensional random feature space to achieve a sufficiently accurate kernel approximation.
