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LIT: Learned Intermediate Representation Training for Model Compression., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 3509-3518. PMLR, (2019)Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark., , , , , , , , , and . ACM SIGOPS Oper. Syst. Rev., 53 (1): 14-25 (2019)TAOBench: An End-to-End Benchmark for Social Networking Workloads., , , , , , , , , and 3 other author(s). Proc. VLDB Endow., 15 (9): 1965-1977 (2022)Accelerating Approximate Aggregation Queries with Expensive Predicates., , , , , and . Proc. VLDB Endow., 14 (11): 2341-2354 (2021)Contracting Wide-area Network Topologies to Solve Flow Problems Quickly., , , , , and . NSDI, page 175-200. USENIX Association, (2021)Storyboard: Optimizing Precomputed Summaries for Aggregation., , and . CoRR, (2020)Online Speculative Decoding., , , , , , and . CoRR, (2023)MLPerf Training Benchmark., , , , , , , , , and 24 other author(s). CoRR, (2019)Jointly Optimizing Preprocessing and Inference for DNN-based Visual Analytics., , , , and . Proc. VLDB Endow., 14 (2): 87-100 (2020)A Demonstration of Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference., , , , , and . Proc. VLDB Endow., 13 (12): 2833-2836 (2020)