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Multi-Way Compressed Sensing for Sparse Low-Rank Tensors.

, and . IEEE Signal Process. Lett., 19 (11): 757-760 (2012)

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Learning Sparse Additive Models with Interactions in High Dimensions., , , and . AISTATS, volume 51 of JMLR Workshop and Conference Proceedings, page 111-120. JMLR.org, (2016)Bipartite Correlation Clustering: Maximizing Agreements., , , and . AISTATS, volume 51 of JMLR Workshop and Conference Proceedings, page 121-129. JMLR.org, (2016)Low-rank regularization and solution uniqueness in over-parameterized matrix sensing., , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 930-940. PMLR, (2020)FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints., , , and . CoRR, (2019)Compressing Gradient Optimizers via Count-Sketches., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5946-5955. PMLR, (2019)Solving hybrid Boolean constraints in continuous space via multilinear Fourier expansions., , , and . Artif. Intell., (2021)Compressive mining: fast and optimal data mining in the compressed domain., , and . VLDB J., 24 (1): 1-24 (2015)Rank-deficient quadratic-form maximization over M-phase alphabet: Polynomial-complexity solvability and algorithmic developments., and . ICASSP, page 3856-3859. IEEE, (2011)How Much Pre-training Is Enough to Discover a Good Subnetwork?, , , , and . Trans. Mach. Learn. Res., (2024)Dropping Convexity for Faster Semi-definite Optimization., , and . COLT, volume 49 of JMLR Workshop and Conference Proceedings, page 530-582. JMLR.org, (2016)