Selected Journal Publication

(* Corresponding author)

  • [Book Chapter] X.-Y. Liu, Y. Fang, L. Yang, Z. Li, A. Walid. High-performance tensor decompositions for compressing and accelerating deep neural networks. Tensors for Data Processing: Theory, Methods, and Applications. [Link] Elsevier; 2021.
  • [Book Chapter] X.-Y. Liu, Reinforcement learning for cyber-physical systems: with cybersecurity case studies. Chapman & Hall/CRC, 2019.
  • [TIT] X.-Y. Liu, S. Aeron, V. Aggarwal*, X. Wang. Low-tubal-rank tensor completion using alternating minimization. IEEE Transactions on Information Theory, 2020.
  • [TNNLS] X.-Y. Liu, Q. Huang, X. Han, B. Wu, L. Kong, A. Walid, and X. Wang*. Real-time decoding of snapshot compressive imaging using tensor FISTA-net. IEEE Transactions on Neural Networks and Learning Systems, 2023.
  • [TNNLS] X.-Y. Liu, X. Wang*. Real-time indoor localization for smartphones using tensor-generative adversarial nets. IEEE Transactions on Neural Networks and Learning Systems, 2020.
  • [TC] X.-Y. Liu, Z. Zhang, Z. Wang, H. Lu, X. Wang, and A. Walid. High-performance tensor learning primitives using GPU tensor cores. IEEE Transactions on Computers, 2022.
  • [TC] H. Huang, X.-Y. Liu*, W. Tong, T. Zhang, A. Walid and X. Wang. High-performance hierarchical Tucker tensor learning using GPU tensor cores. IEEE Transactions on Computers, 2022.
  • [TPDS] T. Zhang, X.-Y. Liu*, and X. Wang. High-Performance GPU tensor completion with tubal-sampling pattern. IEEE Transactions on Parallel and Distributed Systems, 2020.
  • [TPDS] T. Zhang, X.-Y. Liu*, X. Wang, and A. Walid. cuTensor-tubal: Efficient primitives for tubal-rank tensor learning operations on GPUs. IEEE Transactions on Parallel and Distributed Systems, 2019.
  • [TPDS] X.-Y. Liu, Y. Zhu, L. Kong*, C. Liu, Y. Gu, A. V. Vasilakos, M.-Y. Wu. CDC: Compressive data collection for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems,Vol.26, No.8, pp. 2188-2197, 2015. (ESI-Highly Cited)
  • [TPDS] L. Kong, M. Xia, X.-Y. Liu*, G. Chen, Y. Gu, M.-Y. Wu, X. Liu. Data loss and reconstruction in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems,Vol. 25, No. 11, pp. 2818-2828, 2014. (ESI-Highly Cited)
  • [TPDS] L. Kong, M. Zhao, X.-Y. Liu, J. Lu, Y. Liu, M.-Y. Wu, and W. Shu. Surface coverage in sensor networks. IEEE Transactions on Parallel and Distributed Systems, Vol. 25, No. 1, pp. 234-243, 2013.
  • [TMC] X.-Y. Liu, S. Aeron, V. Aggarwal, X. Wang*, M.-Y. Wu. Adaptive sampling of RF fingerprints for fine-grained indoor localization. IEEE Transactions on Mobile Computing, 2016.
  • [TMC] X. Liu, K. Zheng, X.-Y. Liu, X. Wang*, and Y. Zhu. Hierarchical cooperation improves delay in cognitive radio networks with heterogeneous mobile secondary nodes. IEEE Transactions on Mobile Computing, Vol. 18, No. 12, pp. 2871-2884, 2018.
  • [TMC] X. Liu, K. Zheng, L. Fu, X.-Y. Liu, X. Wang*, and G. Dai. Energy efficiency of secure cognitive radio networks with cooperative spectrum sharing. IEEE Transactions on Mobile Computing, Vol. 18, No. 2, pp. 305-318, 2018.
  • [TSP] R. She, P. Fan*, X.-Y. Liu, X. Wang. Interpretable generative adversarial networks with exponential function. IEEE Transactions on Signal Processing, 2021.
  • [ToN] L. Deng, X.-Y. Liu, H. Zheng*, X. Feng, Z. Chen, Graph-tensor neural networks for network traffic data imputation. IEEE Transactions on Networking, 2023.
  • [ToN]  L. Deng, H. Zheng*, X.-Y. Liu, X. Feng, Z. Chen, Network latency estimation with leverage sampling for personal devices: An adaptive tensor completion approach. IEEE Transactions on Networking, 2020.
  • [TITS] L. Deng, X.-Y. Liu, H. Zheng*, X. Feng, Y. Chen. Graph spectral regularized tensor completion for traffic data imputation. IEEE Transactions on Intelligent Transportation Systems, 2021.
  • [TITS] M. Zhu, X.-Y. Liu, X. Wang*. Joint transportation and charging scheduling in public vehicle systems-a game theoretic approach. IEEE Transactions on Intelligent Transportation Systems, 2018.

  • [TITS] M. Zhu, X.-Y. Liu*, X. Wang. An online ride-sharing path planning strategy for public vehicle systems. IEEE Transactions on Intelligent Transportation Systems, 2018.

  • [TITS] M. Zhu, X.-Y. Liu, M. Qiu, W. Shu, F. Tang, R. Shen, M.-Y. Wu. Public vehicles for future urban transportation systems. IEEE Transactions on Intelligent Transportation Systems, 2016.
  • [TBD] X.-Y. Liu, X. Wang*. LS-decomposition for robust recovery of sensory big data. IEEE Transactions on Big Data, 2017.
  • [TALLIP] X.-Y. Liu, Y. Zhang, Y. Liao, and L. Jiang*. Dynamic updating of the knowledge base for a large-scale question answering system. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 19, no. 3, pp. 1-13, 2020.
  • [COMNET] X.-Y. Liu, K.-L. Wu, Y. Zhu, L. Kong, M.-Y. Wu. Mobility increases the surface coverage of distributed sensor networks. Elsevier Computer Networks, 2013.
  • [TGARS] J. Zheng, X.-Y. Liu (co-primary), X. Wang*. Single image cloud removal using U-Net and generative adversarial networks. IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2020.
  • [TIP] T. Geng, X.-Y. Liu*, X. Wang, and G. Sun. Deep shearlet residual learning network for single image super-resolution. IEEE Transactions on Image Processing, 2021.
  • [TIP] P. Yang, L. Kong*, X.-Y. Liu, X. Yuan, and G. Chen. Shearlet enhanced snapshot compressive imaging. IEEE Transactions on Image Processing, 2020.
  • [IoT Journal] J. Yang, C. Fu*, X.-Y. Liu* and A. Walid. Recommendations in Smart Devices Using Federated Tensor Learning. IEEE Internet of Things Journal, 2021. 
  • [IoT Journal] H. Zheng, M. Gao, Z. Zhang, X.-Y. Liu, X. Feng*. An adaptive sampling scheme via approximate volume sampling for fingerprint-based indoor localization. IEEE Internet of Things Journal, 2019.
  • [TNSE] K. Zheng, X.-Y. Liu, L. Fu, X. Wang*, Y. Zhu. Energy efficiency in multihop wireless networks with unreliable links. IEEE Transactions on Network Science and Engineering, 2020.
  • [TNSE] H. Wu, X.-Y. Liu, L. Fu, X. Wang*. Energy-efficient and robust tensor-encoder for wireless camera networks in Internet of Things. IEEE Transactions on Network Science and Engineering, 2018.
  • [TII] L. Kong, X.-Y. Liu, H. Sheng, P. Zeng, and G. Chen. Federated tensor mining for secure industrial Internet of Things. IEEE Transactions on Industrial Informatics, 2019.
  • [TSE] J. Yang, C. Fu*, X.-Y. Liu, H. Yin, P. Zhou. Codee: A tensor embedding scheme for binary code search. IEEE Transactions on Software Engineering, 2021.
  • [TCSS] C. Fu*, Y. Zhao, X.-Y. Liu, J. Yang, A. Walid, and L. T. Yang. Secure tensor decomposition for heterogeneous multimedia data in cloud computing. IEEE Transactions on Computational Social Systems, Vol. 7, no. 1, pp. 247-260, 2020.
  • [TDSC] C. Fu, X.-Y. Liu*, J. Yang, L. T. Yang, S. Yu, and T. Zhu. Wormhole: The hidden virus propagation power of a search engine in social networks. IEEE Transactions on Dependable and Secure Computing, 2017.
  • [TWC] J. Liu, L. Fu, Z. Liu, X.-Y. Liu, and X. Wang*. Interest-aware information diffusion in evolving social networks. IEEE Transactions on Wireless Communications, Vol. 17, no. 7, pp. 4593-4606, 2018.
  • [JPDC] T. Zhang, K. Wan, X.-Y. Liu*. High-performance GPU primitives for graph-tensor learning operations. Elsevier Journal of Parallel Distributed Computing, 2021.
  • [TVT] S. Ma, X.-Y. Liu, L. Fu, X. Tian, X. Gan, X. Wang*. On the greedy resource occupancy threat in dynamic spectrum access. IEEE Transactions on Vehicle Technology, 2017.
  • [TVT] X. Liu, K. Zheng, J. Zhao, X.-Y. Liu, X. Wang*, X. Di. Information-centric networks with correlated mobility. IEEE Transactions on Vehicle Technology, 2017.

For manuscripts

TensorLet@gmail.com
Online contact form

Selected Conference Publication

  • [NeurIPS] X.-Y. Liu, Z. Li, X. Wang. Homomorphic matrix completion. NeurIPS, 2022.
  • [NeurIPS] X.-Y. Liu, Z. Xia, J. Rui, J. Gao, H. Yang, M. Zhu, C. Wang, Z. Wang, J. Guo. FinRL-Meta: Market environments and benchmarks for data-driven financial reinforcement learning. NeurIPS Special Track on Datasets and Benchmarks, 2022.
  • [AAAI] D. Liu, S. Xu, X.-Y. Liu, Z. Xu, W. Wei, P. Zhou. Spatiotemporal graph neural network based mask reconstruction for video object segmentation. AAAI, 2021.
  • [AAAI] X. Han, B. Wu, Z. Shou, X.-Y. Liu*, Y. Zhang, L. Kong. Tensor FISTA-Net for real-time snapshot compressive imaging. AAAI, 2020.
  • [AAAI] F. Jiang, X.-Y. Liu*, H. Lu, R. Shen. Efficient multi-dimensional tensor sparse coding using t-linear combinations. AAAI, 2018. [Slides] and [Poster]
  • [CVPR] M. Yin, S. Liao, X.-Y. Liu, X. Wang, and B. Yuan. Towards extremely compact RNNs for video recognition with fully decomposed hierarchical Tucker structure. CVPR 2021.
  • [ICCV] J. Ma, X.-Y. Liu*, Z. Shou, X. Yuan. Deep tensor ADMM-net for snapshot compressive imaging. ICCV, 2019. [paper].
  • [SIGIR] W. Bao, H. Wen, S. Li, X.-Y. Liu, Q. Lin and K. Yang. GMCM: Graph-based micro-behavior conversion model for post-click conversion rate estimation. SIGIR, Industry Track, 2020. [Slides] and [Video]
  • [WWW] W. Zhang, W. Bao, X.-Y. Liu, K. Yang, Q. Lin, H. Wen, R. Ramezani. Large-scale causal approaches to debiasing post-click conversion rate estimation with multi-task learning. WWW, 2020.
  • [ICAIF] M. Guan, Xiao-Yang Liu*(co-primary). Explainable deep reinforcement learning for portfolio management: An empirical approach. ACM International Conference on AI in Finance,  2021.
  • [ICAIF] Z. Li, Xiao-Yang Liu*(co-primary), J. Zheng, Z. Wang, A. Walid, J. Guo. FinRL-Podracer: High performance and scalable deep reinforcement learning for quantitative finance. ACM International Conference on AI in Finance,  2021.
  • [ICAIF] Xiao-Yang Liu, Hongyang Yang, J. Gao, C. D. Wang. FinRL: Deep reinforcement learning framework to automate trading in quantitative finance. ACM International Conference on AI in Finance,  2021.
  • [ICAIF] Hongyang Yang, Xiao-Yang Liu* (co-primary), S. Zhong, A. Walid, Deep reinforcement learning for automated stock trading: an ensemble strategy. ACM International Conference on AI in Finance,  2020. [PDF]
  • [ICAIF] Q. Chen, Xiao-Yang Liu*, Quantifying ESG alpha using scholar big data: An automated machine learning approach. ACM International Conference on AI in Finance, 2020. [PDF]
  • [BigData] Y. Fang, X.-Y. Liu*, H. Yang. Practical machine learning approach to capture the scholar data driven alpha in AI industry. IEEE Big Data 2019.
  • [ACMMM] Y. Zhang, X.-Y. Liu* (co-primary), B. Wu, A. Walid. Video synthesis via transform-based tensor neural networks. ACM Multimedia, 2020. [Video]
  • [ACMMM] D. Liu, X. Qu, X.-Y. Liu, J. Dong, P. Zhou, Z. Xu. Jointly cross- and self-modal graph attention network for query-based moment localization. ACM Multimedia, 2020.
  • [IJCAI] H. Zhang, Q. Yan, P. Zhou, X.-Y. Liu. Generating robust audio adversarial examples with temporal dependency. IJCAI, 2020.
  • [NeurIPS Workshop] Xiao-Yang Liu, Hongyang Yang, Q. Chen, R. Zhang, L. Yang, B. Xiao, C. D. Wang. FinRL: A deep reinforcement learning library for automated stock trading in quantitative finance. NeurIPS Workshop on Deep Reinforcement Learning, 2020. [PDF]
  • [NeurIPS Workshop] W. Bao, X.-Y. Liu. Spatial influence-aware reinforcement learning for intelligent transportation system. NeurIPS Workshop on Machine Learning for Autonomous Driving, 2019.
  • [NeurIPS Workshop] X.-Y. Liu, Z. Ding, S. Borst, A. Walid. Deep reinforcement learning for intelligent transportation systems. NeurIPS Workshop on Machine Learning for Intelligent Transportation Systems, 2018. [PDF] and [Codes].

  • [NeurIPS Workshop] Z. Xiong, X.-Y. Liu, S. Zhong, H. Yang, A. Walid. Practical deep reinforcement learning approach for stock trading.  NeurIPS  Workshop on Challenges and Opportunities for AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy, 2018. [PDF] and [Codes].

  • [NeurIPS Workshop] W. Lu, X.-Y. Liu, Q. Wu, Y. Sun, A. Walid. Transform-based multilinear dynamical system for tensor time series analysis. NeurIPS Workshop on Modeling and Decision-Making in the Spatiotemporal Domain, 2018. [PDF] and [Codes].

  • [ICML Workshop] X. Li, Y. Li, Y. Zhan, X.-Y. Liu. Optimistic Bull or Pessimistic Bear: adaptive deep reinforcement learning for stock portfolio allocation. ICML Workshop on AI in Finance: Applications and Infrastructure for Multi-Agent Learning, 2019.
  • [ICML Workshop] W. Bao, X.-Y. Liu, Multi-agent reinforcement learning for liquidation strategy analysis. ICML Workshop on AI in Finance: Applications and Infrastructure for Multi-Agent Learning, 2019.
  • [KDD Workshop] X. Li, Y. Li, X.-Y. Liu, D. Wang, Risk management via anomaly circumvent: mnemonic deep learning for midterm stock prediction. KDD Workshop on Anomaly Detection in Finance, 2019.
  • [ICASSP] X.-Y. Liu, T. Zhang (co-primary author). cuTensor-tubal: Optimized GPU library for low-tubal-rank tensors. IEEE ICASSP, 2019.
  • [ICASSP] S. Liao, X.-Y. Liu, F. Qian, M. Yin, G.-M. Hu. Tensor super-resolution for seismic data. IEEE ICASSP, 2019.
  • [ICASSP] C. Li, Y. Sun, X.-Y. Liu, Y. Li. Tensor subspace detection with tubal-sampling and elementwise-sampling. IEEE ICASSP, 2018. [Codes]

  • [ICASSP] F. Jiang, X.-Y. Liu, H. Lu, R. Shen. Anisotropic total variation regularized low-rank tensor completion based on tensor nuclear norm for color image inpainting. IEEE ICASSP, 2018.

  • [ICASSP] X.-Y. Liu, S. Aeron, V. Aggarwal, X. Wang, M.-Y. Wu. Tensor completion via adaptive sampling of tensor fibers: application to efficient indoor RF fingerprinting. IEEE ICASSP, 2016.

  • [ICME] T. Deng, F. Qian,  X.-Y. Liu*, M. Zhang, A. Walid. Tensor sensing for RF tomographic imaging. IEEE ICME, 2018. [Slides] and [Codes]

  • [ICME] F. Jiang, X.-Y. Liu*, H. Lu, R. Shen. Graph regularized tensor sparse coding for image representation. IEEE ICME, 2017.
  • [INFOCOM] L. Kong, M. Xia, X.-Y. Liu, M.-Y. Wu, Xue Liu. Data loss and reconstruction in sensor networks. IEEE INFOCOM, 2013.

  • [MobiHoc] J. Liu, Y. Yao, X. Fu, L. Fu, X.-Y. Liu, X. Wang: Evolving K-graph: Modeling hybrid interactions in networks. MobiHoc, 2017.
  • [ICDCS] L. Kong, L. He, X.-Y. Liu*, Y. Gu, M.-Y. Wu, X. Liu. Privacy-preserving compressive sensing for crowdsensing based trajectory recovery. IEEE ICDCS, Columbus, Ohio, USA, 2015.
  • [IWQoS] M. Zhu, X.-Y. Liu*, M. Qiu, R. Shen, W. Shu, M.-Y. Wu. Traffic Big Data based Path Planning Strategy in Public Vehicle Systems. IEEE IWQoS, 2016.