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Found 9 papers, 2 papers with code
Language Models for Novelty Detection in System Call Traces
Due to the complexity of modern computer systems, novel and unexpected behaviors frequently occur.
Soft Attention: Does it Actually Help to Learn Social Interactions in Pedestrian Trajectory Prediction?
In this paper, we focus on the deep-learning models with a soft-attention mechanism for social interaction modeling and study whether they use social information at prediction time.
Exploring dual information in distance metric learning for clustering
To address these issues, we propose to exploit the dual information associated with the pairwise constraints of the semi-supervised clustering problem.
A Practical Survey on Faster and Lighter Transformers
Recurrent neural networks are effective models to process sequences.
Heuristics for optimizing 3D mapping missions over swarm-powered ad hoc clouds
Drones have been getting more and more popular in many economy sectors.
On Improving Deep Learning Trace Analysis with System Call Arguments
Such tasks may be used to detect anomalies, pre-train neural networks to improve their performance, and extract a contextual representation of the events.
Automatic Cause Detection of Performance Problems in Web Applications
In this paper, we propose a method of extracting the internal behavior of web requests as well as introduce a pipeline that detects performance issues in web requests and provides insights into their root causes.
Empirical comparison between autoencoders and traditional dimensionality reduction methods
The four different dimensionality reduction techniques were separately employed on each dataset to project data into a low-dimensional space.
The Covering-Assignment Problem for Swarm-powered Ad-hoc Clouds: A Distributed 3D Mapping Use-case
Besides automating field operations, a drone swarm can serve as an ad-hoc cloud infrastructure built on top of computing and storage resources available across the swarm members and other connected elements.
