Publications

Zhang, S., G. L. Zhang, B. Li, H. H. Li, and U. Schlichtmann. “Aging-aware Lifetime Enhancement for Memristor-based Neuromorphic Computing.” In Proceedings of the 2019 Design Automation and Test in Europe Conference and Exhibition Date 2019, 1751–56, 2019. https://doi.org/10.23919/DATE.2019.8714954.

Huang, Y. H., Z. Xie, G. Q. Fang, T. C. Yu, H. Ren, S. Y. Fang, Y. Chen, and J. Hu. “Routability-Driven Macro Placement with Embedded CNN-Based Prediction Model.” In Proceedings of the 2019 Design Automation and Test in Europe Conference and Exhibition Date 2019, 180–85, 2019. https://doi.org/10.23919/DATE.2019.8715126.

Joardar, B. K., B. Li, J. R. Doppa, H. Li, P. P. Pande, and K. Chakrabarty. “REGENT: A Heterogeneous ReRAM/GPU-based Architecture Enabled by NoC for Training CNNs.” In Proceedings of the 2019 Design Automation and Test in Europe Conference and Exhibition Date 2019, 522–27, 2019. https://doi.org/10.23919/DATE.2019.8714802.

Fan, Z., Z. Li, B. Li, Y. Chen, and H. H. Li. “RED: A ReRAM-based Deconvolution Accelerator.” In Proceedings of the 2019 Design Automation and Test in Europe Conference and Exhibition Date 2019, 1763–68, 2019. https://doi.org/10.23919/DATE.2019.8715103.

Li, B., B. Yan, and H. Li. “An overview of in-memory processing with emerging non-volatile memory for data-intensive applications.” In Proceedings of the ACM Great Lakes Symposium on VLSI Glsvlsi, 381–86, 2019. https://doi.org/10.1145/3299874.3319452.

Chen, F., L. Song, and H. H. Li. “Efficient process-in-memory architecture design for unsupervised GAN-based deep learning using ReRAM.” In Proceedings of the ACM Great Lakes Symposium on VLSI Glsvlsi, 423–28, 2019. https://doi.org/10.1145/3299874.3319482.

Zhang, J., W. Wen, M. Deisher, H. P. Cheng, H. Li, and Y. Chen. “Learning Efficient Sparse Structures in Speech Recognition.” In ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings, 2019-May:2717–21, 2019. https://doi.org/10.1109/ICASSP.2019.8683620.

Song, L., J. Mao, Y. Zhuo, X. Qian, H. Li, and Y. Chen. “HyPar: Towards hybrid parallelism for deep learning accelerator array.” In Proceedings 25th IEEE International Symposium on High Performance Computer Architecture Hpca 2019, 56–68, 2019. https://doi.org/10.1109/HPCA.2019.00027.

Guo, X., Y. Huang, H. P. Cheng, B. Li, W. Wen, S. Ma, H. Li, and Y. Chen. “Exploration of Automatic Mixed-Precision Search for Deep Neural Networks.” In Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems Aicas 2019, 276–78, 2019. https://doi.org/10.1109/AICAS.2019.8771498.

Ardi, M., A. C. Berg, B. Chen, Y. K. Chen, Y. Chen, D. Kang, J. Lee, et al. “Special Session: 2018 Low-Power Image Recognition Challenge and beyond.” In Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems Aicas 2019, 154–57, 2019. https://doi.org/10.1109/AICAS.2019.8771606.

Li, S., N. Xiao, P. Wang, G. Sun, X. Wang, Y. Chen, H. Li, J. Cong, and T. Zhang. “RC-NVM: Dual-Addressing Non-Volatile Memory Architecture Supporting Both Row and Column Memory Accesses.” IEEE Transactions on Computers 68, no. 2 (February 1, 2019): 239–54. https://doi.org/10.1109/TC.2018.2868368.

Chai, X., X. Fu, Z. Gan, Y. Lu, and Y. Chen. “A color image cryptosystem based on dynamic DNA encryption and chaos.” Signal Processing 155 (February 1, 2019): 44–62. https://doi.org/10.1016/j.sigpro.2018.09.029.

Min, C., J. Mao, H. Li, and Y. Chen. “NeuralHMC: An efficient HMC-based accelerator for deep neural networks.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 432–37, 2019. https://doi.org/10.1145/3287624.3287642.

Li, B., C. Liu, B. Yan, and H. Li. “Build reliable and efficient neuromorphic design with memristor technology.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 224–29, 2019. https://doi.org/10.1145/3287624.3288744.

Cheng, H. P., Q. Wu, J. Shen, H. Li, H. Yang, and Y. Chen. “AdverQuil: An efficient adversarial detection and alleviation technique for black-box neuromorphic computing systems.” In Proceedings of the Asia and South Pacific Design Automation Conference ASP DAC, 557–62, 2019. https://doi.org/10.1145/3287624.3288753.

Chai, X., Z. Gan, K. Yuan, Y. Chen, and X. Liu. “A novel image encryption scheme based on DNA sequence operations and chaotic systems.” Neural Computing and Applications 31, no. 1 (January 18, 2019): 219–37. https://doi.org/10.1007/s00521-017-2993-9.

Hassan, A. M., C. Liu, C. Yang, H. Helen Li, and Y. Chen. “Designing neuromorphic computing systems with memristor devices.” In Handbook of Memristor Networks, 469–94, 2019. https://doi.org/10.1007/978-3-319-76375-0_16.

Yang, C., X. Qiao, and Y. Chen. “Neuromorphic computing systems: From CMOS to emerging nonvolatile memory.” Ipsj Transactions on System Lsi Design Methodology 12 (January 1, 2019): 53–64. https://doi.org/10.2197/IPSJTSLDM.12.53.

Yang, J., X. Wang, Q. Zhou, Z. Wang, H. Li, Y. Chen, and W. Zhao. “Exploiting spin-orbit torque devices as reconfigurable logic for circuit obfuscation.” IEEE Transactions on Computer Aided Design of Integrated Circuits and Systems 38, no. 1 (January 1, 2019): 57–69. https://doi.org/10.1109/TCAD.2018.2802870.

Zheng, Q., J. Kang, Z. Wang, Y. Cai, R. Huang, B. Li, Y. Chen, and H. Li. “Enhance the robustness to time dependent variability of ReRAM-based neuromorphic computing systems with regularization and 2R synapse.” In Proceedings IEEE International Symposium on Circuits and Systems, Vol. 2019-May, 2019. https://doi.org/10.1109/ISCAS.2019.8702756.

Zhou, Y., X. Hu, L. Wang, S. Duan, and Y. Chen. “Markov Chain Based Efficient Defense Against Adversarial Examples in Computer Vision.” IEEE Access 7 (January 1, 2019): 5695–5706. https://doi.org/10.1109/ACCESS.2018.2889409.

Cheng, H. P., P. Yu, H. Hu, S. Zawad, F. Yan, S. Li, H. Li, and Y. Chen. “Towards decentralized deep learning with differential privacy.” In Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 11513 LNCS:130–45, 2019. https://doi.org/10.1007/978-3-030-23502-4_10.

Yang, H., J. Zhang, H. P. Cheng, W. Wang, Y. Chen, and H. Li. “Bamboo: Ball-shape data augmentation against adversarial attacks from all directions.” In Ceur Workshop Proceedings, Vol. 2301, 2019.

Li, Hai, Qiang Tong, and Bo Wang. “Non-negative Matrix Factorization Based Learning from Label Proportions for Vehicle Loan Default Detection.” In Procedia Computer Science, 162:878–86. Elsevier BV, 2019. https://doi.org/10.1016/j.procs.2019.12.063.

Park, J., H. Li, S. Li, W. Wen, Y. Chen, P. T. P. Tang, and P. Dubey. “Faster cnns with direct sparse convolutions and guided pruning.” In 5th International Conference on Learning Representations, ICLR 2017 - Conference Track Proceedings, 2019.