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A Unified View of Kernel k-means, Spectral Clustering and Graph Cuts, , and . TR-04-25. University of Texas Dept. of Computer Science, (2005)Low-rank kernel learning with Bregman matrix divergences, , and . Journal of Machine Learning Research, 10 (Feb): 341--376 (2009)Large-scale Multi-label Learning with Missing Labels., , and . CoRR, (2013)Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization., , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5801-5809. PMLR, (2018)Fast coordinate descent methods with variable selection for non-negative matrix factorization., and . KDD, page 1064-1072. ACM, (2011)Parallel Clustered Low-Rank Approximation of Graphs and Its Application to Link Prediction., , , , , , and . LCPC, volume 7760 of Lecture Notes in Computer Science, page 76-95. Springer, (2012)Convex Perturbations for Scalable Semidefinite Programming., , and . AISTATS, volume 5 of JMLR Proceedings, page 296-303. JMLR.org, (2009)Rank Aggregation and Prediction with Item Features., , and . AISTATS, volume 54 of Proceedings of Machine Learning Research, page 748-756. PMLR, (2017)Computationally Efficient Nyström Approximation using Fast Transforms., , and . ICML, volume 48 of JMLR Workshop and Conference Proceedings, page 2655-2663. JMLR.org, (2016)A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models., , , , and . ICML, volume 37 of JMLR Workshop and Conference Proceedings, page 2418-2426. JMLR.org, (2015)