Search Results for author:
Found 4 papers, 2 papers with code
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension Task
We present an adversarial learning-based domain adaptation framework for the biomedical machine reading comprehension task (BioADAPT-MRC), a neural network-based method to address the discrepancies in the marginal distributions between the general and biomedical domain datasets.
The Sensitivity of Word Embeddings-based Author Detection Models to Semantic-preserving Adversarial Perturbations
To this end, and using those established techniques, we first developed an experimental frame-work for author detection and input perturbations.
Precision Medicine as an Accelerator for Next Generation Cognitive Supercomputing
In the past several years, we have taken advantage of a number of opportunities to advance the intersection of next generation high-performance computing AI and big data technologies through partnerships in precision medicine.
Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources
Apache Calcite is a foundational software framework that provides query processing, optimization, and query language support to many popular open-source data processing systems such as Apache Hive, Apache Storm, Apache Flink, Druid, and MapD.
Databases
