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Found 5 papers, 1 papers with code
A Learning-based Declarative Privacy-Preserving Framework for Federated Data Management
It is challenging to balance the privacy and accuracy for federated query processing over multiple private data silos.
A Comparison of Decision Forest Inference Platforms from A Database Perspective
In addition, the relation-centric representation we proposed significantly improved netsDB's performance in handling large-scale models, while the model reuse optimization we proposed further improved netsDB's performance in handling small-scale datasets.
A Bayesian Approach for Medical Inquiry and Disease Inference in Automated Differential Diagnosis
Unlike previous work that simulates data from given probabilities and uses ML algorithms on them, we directly use the Quick Medical Reference (QMR) belief network, and apply Bayesian inference in the inference phase and Bayesian experimental design in the inquiry phase.
COVID-19: Comparative Analysis of Methods for Identifying Articles Related to Therapeutics and Vaccines without Using Labeled Data
Here we proposed an approach to analyze text classification methods based on the presence or absence of task-specific terms (and their synonyms) in the text.
Robustly Pre-trained Neural Model for Direct Temporal Relation Extraction
Background: Identifying relationships between clinical events and temporal expressions is a key challenge in meaningfully analyzing clinical text for use in advanced AI applications.
