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Boosting Memory Performance of Many-Core FPGA Device through Dynamic Precedence Graph., , , , and . FCCM, page 21-24. IEEE Computer Society, (2013)Stochastic-Based Deep Convolutional Networks with Reconfigurable Logic Fabric., and . IEEE Trans. Multi-Scale Computing Systems, 2 (4): 242-256 (2016)Computationally Efficient Learning of Quality Controlled Word Embeddings for Natural Language Processing., and . ISVLSI, page 134-139. IEEE, (2019)Stochastic-Based Multi-stage Streaming Realization of a Deep Convolutional Neural Network (Abstract Only)., and . FPGA, page 291. ACM, (2017)Coarse-to-fine multi-task training of convolutional neural networks for automated information extraction from cancer pathology reports., , and . BHI, page 218-221. IEEE, (2018)Stochastic-Based Convolutional Networks with Reconfigurable Logic Fabric (Abstract Only)., and . FPGA, page 283. ACM, (2016)Neural network-based fuzzy control surface implementation., , and . GlobalSIP, page 113-117. IEEE, (2015)Stochastic-Based Convolutional Networks with Reconfigurable Logic Fabric., and . ISVLSI, page 713-718. IEEE Computer Society, (2016)Improving memory performance in reconfigurable computing architecture through hardware-assisted dynamic graph., , , and . ReConFig, page 1-8. IEEE, (2013)FIR Filter Based on Stochastic Computing with Reconfigurable Digital Fabric., and . FCCM, page 92-95. IEEE Computer Society, (2015)