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2010
M. Zinkevich, Weimer, M. , Li, L. , and Smola, A. J. , “Parallelized stochastic gradient descent”, Advances in neural information processing systems. pp. 2595–2603, 2010.
2013
M. Mehdi Ghahremanpour, Arab, S. Shahriar, Biookaghazadeh, S. , Zhang, J. , and van der Spoel, D. , “MemBuilder: a web-based graphical interface to build heterogeneously mixed membrane bilayers for the GROMACS biomolecular simulation program”, Bioinformatics, vol. 30, pp. 439–441, 2013. (192.44 KB)
X. Zhang, Huang, M. - C. , Ren, F. , Xu, W. , Guan, N. , and Yi, W. , “Proper Running Posture Guide: A Wearable Biomechanics Capture System”, Proceedings of the 8th International Conference on Body Area Networks (BodyNets). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 2013. (1.54 MB)
X. Zhang, Xu, W. , Huang, M. - C. , Amini, N. , and Ren, F. , “See UV on Your Skin: An Ultraviolet Sensing and Visualization System”, Proceedings of the 8th International Conference on Body Area Networks (BodyNets). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), pp. 22-28, 2013. (1.82 MB)
2014
Y. Shen, Zhu, G. , Li, J. , and Zhu, Z. , “Compressed Sensing Image Reconstruction Algorithm by Dictionary Learning”, Proceedings of International Conference on Internet Multimedia Computing and Service. ACM, p. 193, 2014.
Y. Shen, Zhu, G. , Li, J. , and Zhu, Z. , “Compressed Sensing Image Reconstruction Algorithm by Dictionary Learning”, Proceedings of International Conference on Internet Multimedia Computing and Service. ACM, p. 193, 2014.
Y. Chen, Luo, T. , Liu, S. , Zhang, S. , He, L. , Wang, J. , Li, L. , Chen, T. , Xu, Z. , Sun, N. , and , , “Dadiannao: A machine-learning supercomputer”, Proceedings of the 47th Annual IEEE/ACM International Symposium on Microarchitecture. IEEE Computer Society, pp. 609–622, 2014.
F. Ren, Zhang, C. , Liu, L. , Xu, W. , Owall, V. , and Marković, D. , “A Square-Root-Free Matrix Decomposition Method for Energy-Efficient Least Square Computation on Embedded Systems”, IEEE Embedded Systems Letters, vol. 6, no. 4, pp. 73–76, 2014. (912.74 KB)
2015
S. Biookaghazadeh, Xu, Y. , Zhou, S. , and Zhao, M. , “Enabling scientific data storage and processing on big-data systems”, Big Data (Big Data), 2015 IEEE International Conference on. IEEE, pp. 1978–1984, 2015. (966.13 KB)
S. Biookaghazadeh, Xu, Y. , Zhou, S. , and Zhao, M. , “Enabling scientific data storage and processing on big-data systems”, Big Data (Big Data), 2015 IEEE International Conference on. IEEE, pp. 1978–1984, 2015. (966.13 KB)
Y. Wang, Li, X. , Yu, H. , Ni, L. , Yang, W. , Weng, C. , and Zhao, J. , “Optimizing boolean embedding matrix for compressive sensing in rram crossbar”, Low Power Electronics and Design (ISLPED), 2015 IEEE/ACM International Symposium on. IEEE, pp. 13–18, 2015.
C. Zhang, Li, P. , Sun, G. , Guan, Y. , Xiao, B. , and Cong, J. , “Optimizing fpga-based accelerator design for deep convolutional neural networks”, Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. ACM, pp. 161–170, 2015.
2016
H. Huang, Yu, H. , Zhuo, C. , and Ren, F. , “A Compressive-sensing based Testing Vehicle for 3D TSV Pre-bond and Post-bond Testing Data”, International Symposium on Physical Design (ISPD). pp. 19-25, 2016. (1.21 MB)
2017
S. Biookaghazadeh, “Kaleido: Enabling Efficient Scientific Data Processing on Big-Data Systems”, Networking, Architecture, and Storage (NAS), 2017 International Conference on. IEEE, pp. 1–10, 2017.
S. Biookaghazadeh, “Kaleido: Enabling Efficient Scientific Data Processing on Big-Data Systems”, Networking, Architecture, and Storage (NAS), 2017 International Conference on. IEEE, pp. 1–10, 2017.
W. Li, Zhou, B. , Hsu, C. - Y. , Li, Y. I. , and Ren, F. , “Recognizing terrain features on terrestrial surface using a deep learning model - An example with crater detection”, 1st ACM SIGSPATIAL Workshop on Articial Intelligence and Deep Learning for Geographic Knowledge Discovery. ACM, Los Angeles, CA, pp. 33-36, 2017. (4.93 MB)
2018
S. Biookaghazadeh, Zhao, M. , and Ren, F. , “Are FPGAs Suitable for Edge Computing?”, The USENIX Workshop on Hot Topics in Edge Computing (HotEdge '18). BOSTON, MA, 2018. (363.22 KB)
K. Xu, Zhang, Z. , and Ren, F. , “LAPRAN: A Scalable Laplacian Pyramid Reconstructive Adversarial Network for Flexible Compressive Sensing Reconstruction”, The 15th European Conference on Computer Vision (ECCV'18). Munich, Germany, pp. 491-507, 2018. (1.41 MB)
2019
Y. Feng, Yang, F. , Zhou, X. , Guo, Y. , Tang, F. , Ren, F. , Guo, J. , and Ji, S. , “A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 16, no. 6, pp. 1794-1801, 2019. (1.73 MB)
2020
Y. I. Li, Zhang, S. , Zhou, X. , and Ren, F. , “Build a Compact Binary Neural Network through Bit-level Sensitivity and Data Pruning”, Neurocomputing, vol. 398, pp. 45-54, 2020. (1.91 MB)
Y. I. Li, Zhang, S. , Zhou, X. , and Ren, F. , “Build a Compact Binary Neural Network through Bit-level Sensitivity and Data Pruning”, Neurocomputing, vol. 398, pp. 45-54, 2020. (1.91 MB)
Z. Zhang, Xu, K. , and Ren, F. , “CRA: A Generic Compression Ratio Adaptor for End-to-end Data-driven Image Compressive Sensing Reconstruction Frameworks”, International Conference on Acoustics, Speech, and Signal Processing. Barcelona, Spain, pp. 1740-1749, 2020. (328.74 KB)
F. Ren, Xu, K. , and Zhang, Z. , “LAPRAN: A SCALABLE LAPLACIAN PYRAMID RECONSTRUCTIVE ADVERSARIAL NETWORK FOR FLEXIBLE COMPRESSIVE SENSING RECONSTRUCTION”, 16/745,817, 2020.
X. Zhou, Peng, Y. , Long, C. , Ren, F. , and Shi, C. , “MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time”, The Thirty-seventh International Conference on Machine Learning. Virtual Event, 2020. (9.74 MB)
Y. Wei, Zhou, J. , Wang, Y. , Liu, Y. , Liu, Q. , Luo, J. , Wang, C. , Ren, F. , and Huang, L. , “A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications”, IEEE Transactions on Biomedical Circuits and Systems , vol. 14, no. 2, pp. 145-163, 2020. (2.08 MB)
2021
J. Zhao, Westerham, M. , Lakatos-Toth, M. , Zhang, Z. , Moskoff, A. , and Ren, F. , “OpenICS: Open Image Compressive Sensing Toolbox and Benchmark”, Software Impacts, vol. 9, 2021. (362.26 KB)
J. Zhao, Westerham, M. , Lakatos-Toth, M. , Zhang, Z. , Moskoff, A. , and Ren, F. , “OpenICS: Open Image Compressive Sensing Toolbox and Benchmark”, Software Impacts, vol. 9, 2021. (362.26 KB)
2022
Z. Yu, Trindade, B. Machado, Green, M. , Zhang, Z. , Sneha, P. , Bank-Tavakoli, E. , Pawlowicz, C. , and Ren, F. , “A Data-Driven Approach for Automated Integrated Circuit Segmentation of Scan Electron Microscopy Images”, The 29th IEEE International Conference on Image Processing (ICIP). Bordeaux, France, 2022. (1.03 MB)
Z. Zhang, Zhao, J. , and Ren, F. , “An Experimental Study on Transferring Data-Driven Image Compressive Sensing to Bioelectric Signals”, The 47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Singapore, pp. 1191-1195, 2022. (1.29 MB)
Z. Zhang, Zhao, J. , and Ren, F. , “An Experimental Study on Transferring Data-Driven Image Compressive Sensing to Bioelectric Signals”, The 47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Singapore, pp. 1191-1195, 2022. (1.29 MB)
2023
Z. Zhang, Trindade, B. Machado, Green, M. , Yu, Z. , Pawlowicz, C. , and Ren, F. , “Automatic Error Detection in Integrated Circuits Image Segmentation: A Data-driven Approach”, The 48th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'23). Rhodes Island, Greece, 2023. (501.02 KB)
Z. Zhang, Yu, Z. , You, S. , Rao, R. , Agarwal, S. , and Ren, F. , “Enhanced Low-resolution LiDAR-Camera Calibration Via Depth Interpolation and Supervised Contrastive Learning”, The 48th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'23). Rhodes Island, Greece, 2023. (2.95 MB)