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https://openreview.net/forum?id=WHA8009laxu Federated Learning from Only Unlabeled Data with Class-conditional-sharing Clients | OpenReview Supervised federated learning (FL) enables multiple clients to share the trained model without sharing their labeled data. However, potential clients might... federated learning unlabeled data https://openreview.net/forum?id=Bk4uJPbdWr&referrer=%5Bthe%20profile%20of%20Emmanouil%20Antonios%20Platanios%5D(%2Fprofile%3Fid%3D~Emmanouil_Antonios_Platanios1) Estimating Accuracy from Unlabeled Data: A Probabilistic Logic Approach | OpenReview We propose an efficient method to estimate the accuracy of classifiers using only unlabeled data. We consider a setting with multiple classification problems... unlabeled data probabilistic logic estimating accuracy approach https://deepai.org/publication/explicit-and-implicit-knowledge-distillation-via-unlabeled-data Explicit and Implicit Knowledge Distillation via Unlabeled Data | DeepAI Feb 17, 2023 - 02/17/23 - Data-free knowledge distillation is a challenging model lightweight task for scenarios in which the original dataset is not availa... implicit knowledge unlabeled data explicit distillation via https://deepai.org/publication/unleashing-the-strengths-of-unlabeled-data-in-pan-cancer-abdominal-organ-quantification-the-flare22-challenge Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the... Aug 10, 2023 - 08/10/23 - Quantitative organ assessment is an essential step in automated abdominal disease diagnosis and treatment planning. Artificial int... unlabeled data https://deepai.org/publication/leveraging-unlabeled-data-to-predict-out-of-distribution-performance Leveraging Unlabeled Data to Predict Out-of-Distribution Performance | DeepAI Jan 11, 2022 - 01/11/22 - Real-world machine learning deployments are characterized by mismatches between the source (training) and target (test) distributi... unlabeled data out of leveraging predict distribution https://aclanthology.org/C18-1025/ Joint Learning from Labeled and Unlabeled Data for Information Retrieval - ACL Anthology Bo Li, Ping Cheng, Le Jia. Proceedings of the 27th International Conference on Computational Linguistics. 2018. learning from unlabeled data https://openreview.net/forum?id=jlEjB8MVGa How Does Unlabeled Data Provably Help Out-of-Distribution Detection? | OpenReview Using unlabeled data to regularize the machine learning models has demonstrated promise for improving safety and reliability in detecting out-of-distribution... unlabeled data help out