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Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses.

, , , and . IEEE Trans. Signal Process., (2022)

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Recovering Joint PMF from Pairwise Marginals., and . ACSSC, page 356-360. IEEE, (2020)Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms., , , and . NeurIPS, page 7845-7855. (2019)Deep Learning From Crowdsourced Labels: Coupled Cross-Entropy Minimization, Identifiability, and Regularization., , and . ICLR, OpenReview.net, (2023)Fiber-Sampled Stochastic Mirror Descent for Tensor Decomposition with β-Divergence., , , and . ICASSP, page 2925-2929. IEEE, (2021)Deep Learning from Noisy Labels via Robust Nonnegative Matrix Factorization-Based Design., , , and . CAMSAP, page 446-450. IEEE, (2023)Learning From Crowdsourced Noisy Labels: A Signal Processing Perspective., , , and . CoRR, (2024)Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses., , , and . CoRR, (2021)Mixed Membership Graph Clustering via Systematic Edge Query., and . CoRR, (2020)Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 25980-26007. PMLR, (2023)Crowdsourcing via Annotator Co-occurrence Imputation and Provable Symmetric Nonnegative Matrix Factorization., and . ICML, volume 139 of Proceedings of Machine Learning Research, page 4544-4554. PMLR, (2021)