[J15] Qingqiang He, Xu Jiang, Nan Guan, and Zhishan Guo. A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for portfolio optimization. Information retrieval from large data sets via multiple-winners-take-all. (13) to 15% of the shorter side of image. TREC Video Retrieval Evaluation - National Institute of Standards and Technology (TRECVid), July 2007. Leibniz-Zentrum fur Informatik, 2014. 2019. Proceedings of IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Torino, Italy, Sept. 2018. Optimizing Energy in Non-preemptive Mixed-Criticality Scheduling by Exploiting Probabilistic Information. 47, no. Ph.D. Thesis in CpE at UCF, 2020 (Co-advisor: Haoyi Xiong at Missouri S&T and Baidu Inc.) Current Ph. A one-layer recurrent neural network for pseudoconvex optimization with linear equality constraints. The Safe and Effective Application of Probabilistic Techniques in Safety-Critical Systems. 120-125, 2017. [C42] Jasdeep Singh, Luca Santinelli, Federico Reghenzani, Konstantinos Bletsas, David Doose, Zhishan Guo. EDF-Based Mixed-Criticality Scheduling with Graceful Degradation by Bounded Lateness. This calendar lists graduate thesis and dissertation defenses. ACM Transactions on Embedded Computing Systems (TECS), vol. Alexandra French, Zhishan Guo, and Sanjoy Baruah. D. Dissertation Supervised Jiang Bian, Statistical and Stochasticity Learning Algorithms for Distributed and Intelligent Systems. [C33] Zhishan Guo, Luca Santinelli, and Kecheng Yang. JIANG BIAN | Orlando, Florida | Student at University of Central Florida | 48 connections | View JIANG's homepage, profile, activity, articles Leibniz International Proceedings in Informatics, Schloss Dagstuhl --- Leibniz Center for Informatics. [C12] Sanjoy Baruah` and Zhishan Guo`. [J25] Yang Wang, Jiang Xu, Nan Guan, Zhishan Guo, Xue Liu, and Wang Yi. 31, no. [C43] Ashikahmed Bhuiyan*^, Kecheng Yang*, Samsil Arefin, Abusayeed Saifullah, Nan Guan, and Zhishan Guo. [C35] Xin Han, Liang Zhao, Zhishan Guo, and Xingwu Liu. 2283 - 2295, 2019. [J10] Jinghao Sun, Nan Guan, Xu Jiang, Shuangshuang Chang, Zhishan Guo, Qingxu Deng, and Wang Yi . An Improved Speedup Factor for Sporadic Tasks with Constrained Deadlines under Dynamic Priority Scheduling. 353-360, 2015. Zhishan Guo. 14, no. 4, pp. [C26] Luca Santinelli and Zhishan Guo. 12, pp. 2018. Efficient Feasibility Analysis for Graph-based Real-Time Task Systems. ShanghaiTechA and UCF CC 50 where image resolutions are smaller, and 512 512 for ShanghaiTechB and UCF-QNRF. [C31] Haoyi Xiong, Wei Cheng, Wenqing Hu, Jiang Bian, Yanjie Fu, and Zhishan Guo. [J1] Wenbing Xu and Zhishan Guo. Tsinghua University Honors Undergraduate Thesis (with excellence award), 2009. Announcing the Final Examination of Jiang Bian for the degree of Doctor of Philosophy Time & Location: November 9, 2020 at 2:00 PM in remote https://… | Graduate Thesis and Dissertation Defenses To help minimize the spread of COVID-19, some events are being offered virtually, and in-person events have additional safety requirements. Real-Time Scheduling Open Problems Seminar (RTSOPS), Barcelona, Spain, July 2018. Yongliang Yang Associate Professor, University of Science and Technology Beijing Verified email at ustb.edu.cn. Sai Sruti^, Ashikahmed Bhuiyan, and Zhishan Guo. International Journal of Hospitality Management, 91(102660), 2020. Proceedings of the 3rd Symposium on Dependable Software Engineering: Theories, Tools and Applications (SETTA), Changsha, China, Oct. 2017. 238-248, 2016. DBSDA: Lowering the Error Bound of Sparse Linear Discriminant Analysis via Model De-Biasing. Our purpose is to provide Florida state employee salary figures in the name of transparency for taxpayers. Implementing mixed-criticality systems upon a preemptive varying-speed processor. [C14] Zhishan Guo`, Luca Santinalli`, and Kecheng Yang`. Jasdeep Singh, Luca Santinelli, Zhishan Guo, Julien Brunel, David Doose, and Guillaume Infantes. Jinhui Yuan, et al. [J5] Zhishan Guo and Sanjoy Baruah. Proceedings of the 14th International Symposium on Neural Networks (ISNN), Sapporo, Japan, June 2017. Sanjoy Baruah and Zhishan Guo. The system can't perform the operation now. Scheduling mixed-criticality systems to guarantee some service under all non-erroneous behaviors. D. student of Computer Engineering, UCF‬ - ‪Cited by 43‬ - ‪Cyber Physical Systems‬ - ‪Ubiquitous Computing‬ Fig. Search for more papers by this author. Nature Genetics, vol. THU and ICRC at TRECVID 2008. Predicting lower limb 3D kinematics during gait using reduced number of wearable sensors via deep learning. IEEE Transactions on Parallel and Distributed Systems (TPDS), to appear, 2021. Proceeding of the 33rd AAAI Conference on Artificial Intelligence (AAAI), Honolulu, USA, Feb. 2019. GARDS: Generalized Autonomous Robotic Delivery System. [C44] Li Li*, Haoyi Xiong*, Jun Wang, Chengzhong Xu, and Zhishan Guo. 1-27, 2016. Proceeding of IEEE International Conference on Big Data (IEEE BigData 2019), Los Angeles, CA, Dec. 2019. Control allocation of flying-wing with multi-effectors based on TS fuzzy model. An effective dimension reduction approach in Chinese document classification using Genetic Algorithm. Florida Salaries provides an easily searchable database of names, classes, and salaries for individuals who have been employed by Florida State agencies and universities. SmartPC: Hierarchical Pace Control in Real-Time Federated Learning System. University of Florida, USA. ‪Graduate Center, City University of New York‬ - ‪880 lần trích dẫn‬ - ‪Social Networks‬ - ‪Text Mining‬ - ‪Applied Psychometrics‬ - ‪Big Data‬ - ‪Computational Psychology‬ International Conference on Embedded Software (EMSOFT), Torino, Italy, Oct. 2018. Proceedings of the 36th IEEE Real-Time Systems Symposium (RTSS), Workshop on Mixed-Criticality Systems, San Antonio, USA, Dec. 2015. [J7] Wei Cheng, Zhishan Guo, Xiang Zhang, and Wei Wang. AWDA: An adaptive wishart discriminant analysis, Work-in-Progress: A Deep Learning Strategy for I/O Scheduling in Storage Systems, Priority-based Multi-Flight Path Planning with Uncertain Sector Capacities, Improving covariance-regularized discriminant analysis for EHR-based predictive analytics of diseases, CRLEDD: Regularized Causalities Learning for Early Detection of Diseases Using Electronic Health Record (EHR) Data, COMO: Widening Deep Neural Networks with COnvolutional MaxOut, On Generating Dominators of Customer Preferences, FWDA: a Fast Wishart Discriminant Analysis with its Application to Electronic Health Records Data Classification. Authors: Huaizu Jiang, Zejian Yuan, Ming-Ming Cheng, Yihong Gong, Nanning Zheng, Jingdong Wang Subjects: Computer Vision and Pattern Recognition (cs.CV) [29] arXiv:1310.4389 [ pdf , other ] Parametric sensitivity and scalability of k-winners-take- all networks. Jiang Bian. On Generating Dominators of Customer Preferences. Use of probabilities and formal methods to control system criticality levels. Zhishan Guo. MP2SDA: Multi-Party Parallelized Sparse Discriminant Learning. Metric learning from relative comparisons by minimizing squared residual. Sampling Sparse Representations with Randomized Measurement Langevin Dynamics. Mixed-criticality job models: a comparison. Jihoon Seo, SungKyung Kim, Beomjoon Chae, Jaewon Lee : 3: UCSD-Sid: Siddharth Saha [J20] Haoyi Xiong, Jiang Bian^, Zhishan Guo, Chengzhong Xu, and Dejing Dou. PDF access and copyright: The copyrights to many of the publications listed here belong to the publishers. Mixed Criticality Scheduling of Probabilistic Real-Time Systems. AWDA: An Adaptive Wishart Discriminant Analysis. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. Zhishan Guo, Ying Zhang, Lingxiang Wang, and Zhenkai Zhang. 30, no. IEEE Transactions on Multimedia (TMM), to appear, 2020. De-biasing Covariance-Regularized Discriminant Analysis, DRESS: Dynamic RESource-reservation Scheme for Congested Data-intensive Computing Platforms, Sustainability in Mixed-Criticality Scheduling, AWDA: An Adaptive Wishart Discriminant Analysis, On the Criticality of Probabilistic Worst-Case Execution Time Models, Handling Write Backs in Multi-Level Cache Analysis for WCET Estimation, Integrating Cache-Related Preemption Delay into Global-EDF Analysis for Multiprocessor Scheduling, Response Time in Mixed-Critical Pervasive Systems, Off-policy Reinforcement Learning for Robust Control of Discrete-time Uncertain Linear Systems, Energy-Efficient Multi-Core Scheduling for Real-Time DAG Tasks, Hamiltonian-driven Adaptive Dynamic Programming based on Extreme Learning Machine, Mixed-criticality scheduling to minimize makespan, Fault-Aware Sensitivity Analysis for Probabilistic Real-Time Systems, Scheduling mixed-criticality systems to guarantee some service under all non-erroneous behaviors, MC-Fluid: simplified and optimally quantified, The concurrent consideration of uncertainty in WCETs and processor speeds in mixed criticality systems, EDF schedulability analysis on mixed-criticality systems with permitted failure probability, Uniprocessor EDF scheduling of AVR task systems, Scheduling mixed-criticality implicit-deadline sporadic task systems upon a varying-speed processor, Mixed-criticality scheduling upon varying-speed multiprocessors, Graph Regularized Dual Lasso for Robust eQTL Mapping, Mixed-criticality scheduling upon varying-speed processors, Flexible and Robust Co-regularized Multi-Domain Graph Clustering, Mixed-criticality scheduling upon non-monitored varying-speed processors, Metric learning from relative comparisons by minimizing squared residual, Information retrieval from large data sets via multiple-winners-take-all, Control allocation of flying-wing with multi-effectors based on TS fuzzy model, A neurodynamic optimization approach to constrained sparsity maximization based on alternative objective functions, Parametric sensitivity and scalability of k-winners-take- all networks, An effective dimension reduction approach in Chinese document classification using Genetic Algorithm, Real-Time Scheduling of Mixed-Critical Workloads upon Platforms with Uncertainties, A Neurodynamic Optimization Approach to Constrained Pseudoconvex Optimization, GARDS: Generalized Autonomous Robotic Delivery System, A Deep Learning Strategy for I/O Scheduling in Storage Systems, Resource Augmentation Bounds of EDF and Partitioned-EDF for Sporadic Tasks with Constrained Deadlines, Use of probabilities and formal methods to control system criticality levels, RWS - A Roulette Wheel Scheduler For Preventing Execution Pattern Leakage, Cache-Aware Partitioned EDF Scheduling for Multi-Core Real-Time Systems, Guaranteeing some service upon mode switch in mixed-criticality systems, Regarding the Optimality of Speedup Bounds of Mixed-Criticality Schedulability Tests, Mixed-criticality scheduling on varying-speed platforms with bounded performance dropping rate, Mixed-criticality job models: a comparison, MC Scheduling on Varying-Speed Processors, Scheduling mixed-criticality workloads upon unreliable processors.