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Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels., , , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 485-493. JMLR.org, (2014)CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery., , , , , , , , , and 1 other author(s). CoRR, (2020)Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems., , , , and . CoRR, (2019)Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems., , , and . KDD, page 165-175. ACM, (2020)Implementing Randomized Matrix Algorithms in Parallel and Distributed Environments., , and . CoRR, (2015)Tensor machines for learning target-specific polynomial features., and . CoRR, (2015)Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels., , , and . J. Mach. Learn. Res., (2016)Modeling and online control of generalized energy storage networks., , , and . e-Energy, page 27-38. ACM, (2014)Sub-sampled Newton Methods with Non-uniform Sampling., , , , and . NIPS, page 3000-3008. (2016)Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale., , , , , , , , , and 12 other author(s). WWW (Companion Volume), page 73-82. ACM, (2024)