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Found 8 papers, 2 papers with code
Eliminating Backdoors in Neural Code Models via Trigger Inversion
EliBadCode first filters the model vocabulary for trigger tokens to reduce the search space for trigger inversion, thereby enhancing the efficiency of the trigger inversion.
Benchmarking Robustness of AI-Enabled Multi-sensor Fusion Systems: Challenges and Opportunities
Multi-Sensor Fusion (MSF) based perception systems have been the foundation in supporting many industrial applications and domains, such as self-driving cars, robotic arms, and unmanned aerial vehicles.
Measuring Discrimination to Boost Comparative Testing for Multiple Deep Learning Models
To tackle this problem, we propose Sample Discrimination based Selection (SDS) to select efficient samples that could discriminate multiple models, i. e., the prediction behaviors (right/wrong) of these samples would be helpful to indicate the trend of model performance.
IEO: Intelligent Evolutionary Optimisation for Hyperparameter Tuning
In this paper, we introduce an intelligent evolutionary optimisation algorithm which applies machine learning technique to the traditional evolutionary algorithm to accelerate the overall optimisation process of tuning machine learning models in classification problems.
Connecting Software Metrics across Versions to Predict Defects
Accurate software defect prediction could help software practitioners allocate test resources to defect-prone modules effectively and efficiently.
Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning
In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD^2L) approach for SR person re-identification.
Link Prediction in Social Networks: the State-of-the-Art
Finally, some future challenges of the link prediction in social networks are discussed.
Social and Information Networks Physics and Society
A Feature Subset Selection Algorithm Automatic Recommendation Method
The performance of the candidate FSS algorithms is evaluated by a multi-criteria metric that takes into account not only the classification accuracy over the selected features, but also the runtime of feature selection and the number of selected features.
