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Found 6 papers, 1 papers with code
Sparse Winograd Convolutional neural networks on small-scale systolic arrays
The reconfigurability, energy-efficiency, and massive parallelism on FPGAs make them one of the best choices for implementing efficient deep learning accelerators.
Deep Spectral Q-learning with Application to Mobile Health
Dynamic treatment regimes assign personalized treatments to patients sequentially over time based on their baseline information and time-varying covariates.
Prediction of COVID-19 Patients' Emergency Room Revisit using Multi-Source Transfer Learning
Results showed that the Multi-DANN models outperformed the Single-DANN models and baseline models in predicting revisits of COVID-19 patients to the ER within 7 days after discharge.
A Survey of Heterogeneous Transfer Learning
These methods typically presuppose identical feature spaces and label spaces in both domains, known as homogeneous transfer learning, which, however, is not always a practical assumption.
Large Language Model for Causal Decision Making
Large Language Models (LLMs) have shown their success in language understanding and reasoning on general topics.
Online Transfer Learning for RSV Case Detection
Transfer learning has become a pivotal technique in machine learning and has proven to be effective in various real-world applications.
