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CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery., , , , , , , , , and 1 other author(s). CoRR, (2020)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)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)Quantile Regression for Large-scale Applications., , and . ICML (3), volume 28 of JMLR Workshop and Conference Proceedings, page 881-887. JMLR.org, (2013)Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale., , , , , , , , , and 12 other author(s). CoRR, (2023)Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems., , , , and . ISIT, page 2786-2791. IEEE, (2021)Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems., , , , , , , , , and 5 other author(s). CoRR, (2020)Feature-distributed sparse regression: a screen-and-clean approach., , , and . NIPS, page 2712-2720. (2016)Towards the Better Ranking Consistency: A Multi-task Learning Framework for Early Stage Ads Ranking., , , , , , , , , and 3 other author(s). AdKDD@KDD, volume 3556 of CEUR Workshop Proceedings, CEUR-WS.org, (2023)