Search Results for author:
Found 2 papers, 0 papers with code
Uncertainty-Aware Multi-View Representation Learning
Under the help of uncertainty, DUA-Nets weigh each view of individual sample according to data quality so that the high-quality samples (or views) can be fully exploited while the effects from the noisy samples (or views) will be alleviated.
Memory-Efficient Factorization Machines via Binarizing both Data and Model Coefficients
Our proposed method can significantly reduce the memory cost of SEFM model.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
