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A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models., , , , и . ICML, том 37 из JMLR Workshop and Conference Proceedings, стр. 2418-2426. JMLR.org, (2015)Learning Tensor Latent Features., , , , и . CoRR, (2018)Minimizing FLOPs to Learn Efficient Sparse Representations., , , , , и . ICLR, OpenReview.net, (2020)Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space., , , , и . NIPS, стр. 2456-2464. (2014)MagicDec: Breaking the Latency-Throughput Tradeoff for Long Context Generation with Speculative Decoding., , , , , , и . CoRR, (2024)Latent Feature Lasso., , , , , и . ICML, том 70 из Proceedings of Machine Learning Research, стр. 3949-3957. PMLR, (2017)Loss Decomposition for Fast Learning in Large Output Spaces., , , , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 5626-5635. PMLR, (2018)S4: a High-sparsity, High-performance AI Accelerator., , и . CoRR, (2022)Tackling the Achilles Heel of Social Networks: Influence Propagation based Language Model Smoothing., , , , и . WWW, стр. 1318-1328. ACM, (2015)Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding., , , , , , , и . KDD, стр. 1418-1428. ACM, (2019)