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2020 – today
- 2023
[j5]Zilong Tan, Juan Zhang, Yuqing Yan, Jiayue Sun, Huaguang Zhang:
Fully distributed dynamic event-triggered output regulation for heterogeneous linear multiagent systems under fixed and switching topologies. Neural Comput. Appl. 35(16): 11753-11771 (2023)- [j4]Jiayue Sun
, Zilong Tan, Shu Liu, Huaguang Zhang, Wenyu Chuo:
Fully Distributed Event-Driven Coordination With Actuator Faults. IEEE Trans. Cybern. 53(10): 6456-6464 (2023) - 2022
- [j3]Zilong Tan, Yang Liu, Jiayue Sun, Huaguang Zhang, Xiangpeng Xie:
Chaos synchronization control for stochastic nonlinear systems of interior PMSMs based on fixed-time stability theorem. Appl. Math. Comput. 430: 127115 (2022) - [j2]Pengda Liu, Huaguang Zhang, Jiayue Sun, Zilong Tan:
Event-triggered adaptive integral reinforcement learning method for zero-sum differential games of nonlinear systems with incomplete known dynamics. Neural Comput. Appl. 34(13): 10775-10786 (2022) - 2021
- [c5]Bing Xie, Zilong Tan, Philip H. Carns, Jeffrey S. Chase, Kevin Harms, Jay F. Lofstead, Sarp Oral, Sudharshan S. Vazhkudai, Feiyi Wang:
Interpreting Write Performance of Supercomputer I/O Systems with Regression Models. IPDPS 2021: 557-566 - 2020
- [c4]Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar:
Learning Fair Representations for Kernel Models. AISTATS 2020: 155-166 - [i6]Abhishek Kumar Dubey, Alina Peluso, Jacob D. Hinkle, Devanshu Agarawal, Zilong Tan:
Model Reduction of Shallow CNN Model for Reliable Deployment of Information Extraction from Medical Reports. CoRR abs/2008.01572 (2020)
2010 – 2019
- 2019
- [c3]Bing Xie, Zilong Tan, Philip H. Carns, Jeffrey S. Chase, Kevin Harms, Jay F. Lofstead, Sarp Oral, Sudharshan S. Vazhkudai, Feiyi Wang:
Applying Machine Learning to Understand Write Performance of Large-scale Parallel Filesystems. PDSW@SC 2019: 30-39 - [i5]Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar:
Learning Fair Representations for Kernel Models. CoRR abs/1906.11813 (2019) - 2018
- [b1]Zilong Tan:
Approximate Inference for High-Dimensional Latent Variable Models. Duke University, Durham, NC, USA, 2018 - [c2]Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee:
Scalable Algorithms for Learning High-Dimensional Linear Mixed Models. UAI 2018: 259-268 - [i4]Zilong Tan, Sayan Mukherjee:
Learning Integral Representations of Gaussian Processes. CoRR abs/1802.07528 (2018) - [i3]Zilong Tan, Kimberly Roche, Xiang Zhou, Sayan Mukherjee:
Scalable Algorithms for Learning High-Dimensional Linear Mixed Models. CoRR abs/1803.04431 (2018) - 2017
- [c1]Zilong Tan, Sayan Mukherjee:
Partitioned Tensor Factorizations for Learning Mixed Membership Models. ICML 2017: 3358-3367 - [i2]Zilong Tan, Sayan Mukherjee:
Efficient Learning of Graded Membership Models. CoRR abs/1702.07933 (2017) - 2016
- [j1]Zilong Tan, Shivnath Babu:
Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases. Proc. VLDB Endow. 9(10): 720-731 (2016) - 2015
- [i1]Zilong Tan, Shivnath Babu:
Tempo: Robust and Self-Tuning Resource Management in Multi-tenant Parallel Databases. CoRR abs/1512.00757 (2015)
Coauthor Index
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