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Training Deep Neural Networks with Joint Quantization and Pruning of Weights and Activations., , , and . CoRR, (2021)Human-Like Navigation Behavior: A Statistical Evaluation Framework., and . CoRR, (2022)A2Q+: Improving Accumulator-Aware Weight Quantization., , , and . CoRR, (2024)A2Q: Accumulator-Aware Quantization with Guaranteed Overflow Avoidance., , and . ICCV, page 16943-16952. IEEE, (2023)AX-DBN: An Approximate Computing Framework for the Design of Low-Power Discriminative Deep Belief Networks., , and . IJCNN, page 1-9. IEEE, (2019)PT-MMD: A Novel Statistical Framework for the Evaluation of Generative Systems., , , , and . ACSSC, page 2219-2223. IEEE, (2019)A Competitive Edge: Can FPGAs Beat GPUs at DCNN Inference Acceleration in Resource-Limited Edge Computing Applications?, , , and . CoRR, (2021)Generating GPU Compiler Heuristics using Reinforcement Learning., , and . CoRR, (2021)Generative and Discriminative Deep Belief Network Classifiers: Comparisons Under an Approximate Computing Framework., , , and . CoRR, (2021)Robust Transferable Feature Extractors: Learning to Defend Pre-Trained Networks Against White Box Adversaries., , and . CoRR, (2022)