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Memristive logic: A framework for evaluation and comparison., , , , , , and . PATMOS, page 1-8. IEEE, (2017)TenSet: A Large-scale Program Performance Dataset for Learned Tensor Compilers., , , , , , and . NeurIPS Datasets and Benchmarks, (2021)AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning., , , , , , and . MLSys, mlsys.org, (2020)Machine Learning in Compiler Optimization.. University of California, Berkeley, USA, (2020)IMAGING: In-Memory AlGorithms for Image processiNG., , , , and . IEEE Trans. Circuits Syst. I Regul. Pap., 65-I (12): 4258-4271 (2018)RLDRM: Closed Loop Dynamic Cache Allocation with Deep Reinforcement Learning for Network Function Virtualization., , , , , , , , , and 1 other author(s). NetSoft, page 335-343. IEEE, (2020)SIMPLER MAGIC: Synthesis and Mapping of In-Memory Logic Executed in a Single Row to Improve Throughput., , , , , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 39 (10): 2434-2447 (2020)AutoCkt: Deep Reinforcement Learning of Analog Circuit Designs., , , , and . DATE, page 490-495. IEEE, (2020)Practical challenges in delivering the promises of real processing-in-memory machines., , , , , , and . DATE, page 1628-1633. IEEE, (2018)Efficient Algorithms for In-Memory Fixed Point Multiplication Using MAGIC., , , and . ISCAS, page 1-5. IEEE, (2018)