8 citations · 23 across the 6 of their papers we have counts for
Showing 2022 · cs.LGShow all
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cs.LG2022★ 7 cited
Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training
Derek Everett, Andre T. Nguyen, Luke E. Richards +1
The quantification of uncertainty is important for the adoption of machine learning, especially to reject out-of-distribution (OOD) data back to human experts for review. Yet progr…
cs.LG2022★ 8 cited
FedSPLIT: One-Shot Federated Recommendation System Based on Non-negative Joint Matrix Factorization and Knowledge Distillation
Maksim E. Eren, Luke E. Richards, Manish Bhattarai +3
Non-negative matrix factorization (NMF) with missing-value completion is a well-known effective Collaborative Filtering (CF) method used to provide personalized user recommendation…