研究概要

主要論文

• 1. Li, C., Khan, M. E., Sun, Z., Niu, G., Han, B., Xie, S., and Zhao, Q.:
  "Beyond unfolding: Exact recovery of latent convex tensor decomposition under reshuffling"
  Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pp.4602-4609, 2020
• 2. Wang, A., Li, C., Jin, Z., and Zhao, Q.:
  "Robust tensor decomposition via orientation invariant tubal nuclear norms"
  Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), pp.6102-6109, 2020
• 3. Hou, M., Tang, J., Zhang, J., Kong, W., and Zhao, Q.:
  "Deep multimodal multilinear fusion with high-order polynomial pooling"
  Advances in Neural Information Processing Systems 32 (NeurIPS 2019), pp.12136-12145, 2019.
• 4. Liang, P., Liu, Z., Tsai, Y., Zhao, Q., Salakhutdinov, R., and Morency, L.:
  "Learning Representations from Imperfect Time Series Data via Tensor Rank Regularization"
  Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), pp.1569–1576, 2019.
• 5. Li, C., He, W., Yuan, L., Sun, Z., and Zhao, Q.:
  "Guaranteed Matrix Completion Under Multiple Linear Transformations"
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp.11128-11137, 2019
• 6. He, W., Yao, Q., Li, C., Yokoya, N., and Zhao, Q.:
  "Non-Local Meets Global: An Integrated Paradigm for Hyperspectral Denoising"
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6861-6870, 2019
• 7. Yuan, L., Li, C., Mandic, D., Cao, J., and Zhao, Q.:
  "Tensor ring decomposition with rank minimization on latent space: An efficient approach for tensor completion"
  The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), pp.9151-9158, 2019.
• 8. Zhao, Q., Zhou, G., Zhang, L., Cichocki, A., and Amari, S.:
  "Bayesian robust tensor factorization for incomplete multiway data"
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 27(4):736-748, 2016.
• 9. Zhao, Q., Zhang, L., and Cichocki, A.:
  "Bayesian CP factorization of incomplete tensors with automatic rank determination"
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 37(9):1751-1763, 2015.
• 10. Zhao, Q., Caiafa, C. F., Mandic, D. P., Zhang, L., Ball, T., Schulze-Bonhage, A., and Cichocki, A.:
  "Multilinear subspace regression: an orthogonal tensor decomposition approach"
  Advances in Neural Information Processing Systems 24 (NIPS), pp. 1269-1277, 2011.

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