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On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks.

, , , , and . NeurIPS, page 13888-13899. (2019)

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Automatic Evolution of Parallel Sorting Programs on Multi-cores., , and . EvoApplications, volume 9028 of Lecture Notes in Computer Science, page 706-717. Springer, (2015)On the efficiency of Multi-core Grammatical Evolution (MCGE) evolving multi-core parallel programs., , and . NaBIC, page 238-243. IEEE, (2014)Distributed non-negative matrix factorization with determination of the number of latent features., , , , and . J. Supercomput., 76 (9): 7458-7488 (2020)Learning When to Trust Which Teacher for Weakly Supervised ASR., , , , and . CoRR, (2023)Modeling Shared Cache Performance of OpenMP Programs using Reuse Distance., , , , and . CoRR, (2019)Federated Self-Learning with Weak Supervision for Speech Recognition., , , , , , and . ICASSP, page 1-5. IEEE, (2023)ILASR: Privacy-Preserving Incremental Learning for Automatic Speech Recognition at Production Scale., , , , , , , , , and 4 other author(s). KDD, page 2780-2788. ACM, (2022)Predict the performance of GE with an ACO based machine learning algorithm., , and . GECCO (Companion), page 1353-1360. ACM, (2014)Combating Label Noise in Deep Learning using Abstention., , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 6234-6243. PMLR, (2019)Synthesis of Parallel Programs on Multi-Cores., , , , and . Handbook of Grammatical Evolution, Springer, (2018)