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代表性成果(* 通讯作者):

  • Fanhua Shang, Yuanyuan Liu*, Kaiwen Zhou, James Cheng, Kelvin Kai Wing Ng, and Yuichi Yoshida. Guaranteed Sufficie Decrease for Stochastic Variance Reduced Gradient Optimization.  In: Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 2018.
  • Yuanyuan Liu, Fanhua Shang, James Cheng, Hong Cheng, and Licheng Jiao. Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds. In: Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS)pp. 4875-4884, 2017. (CCF A).
  • Yuanyuan Liu, Fanhua Shang, and James Cheng. Accelerted Variance Reduced Stochastic ADMM.  In: Proceedings of the 31st AAAI Conference on Artificial Intelligence AAAIpp. 2287-2293 ,  2017. (CCF A).
  • Yuanyuan Liu, Fanhua Shang, Wei Fan, James Cheng, and Hong Cheng. Generalized Higher-Order Orthogonal Iteraton for Tensor Learning and Decomposition. IEEE Transactions on Neural Networks and Learning Systems, vol. 27, no. 12, pp. 2551-2563, 2016. ( IF: 7.982中科院分区1区).
  • Yuanyuan Liu, Fanhua Shang, Licheng Jiao, James Cheng, and Hong Cheng. Trace Norm Regularized CANDECOMP/PARAFAC Decoposition with Missing Data.  IEEE Transaction on Cybernetics, vol. 45, no. 11, pp. 2437-2448, 2015.(IF: 8.803,中科院分区1分区).
  • Fanhua Shang*, Yuanyuan Liu*, James Cheng, Zhi-Quan Luo, and Zhouchen Lin. Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications. To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017.(IF: 9.455,中科院分区1分区)
  • Fanhua Shang, Yuanyuan Liu, James Cheng, and Da Yan. Fuzzy Double Trace Norm Minimization for Recommendation Systems. To appear in IEEE Transactions on Fuzzy Systems, 2017. (IF: 8.415,中科院分区1分区 ).
  • Fanhua Shang,  Yuanyuan Liu, and James Cheng. Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization. In: Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 2016.
  • Fanhua Shang,Yuanyuan Liu, James Cheng. Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI), 2016. (CCF A).
  • Yuanyuan Liu,Fanhua Shang,Wei Fan, James Cheng, and Hong Cheng. Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion. In: Proceedings of the Annual Conference on Neural Information Processing Systems (NIPS)pp.1763-1771, 2014. (CCF A)
  • Fanhua Shang,Yuanyuan Liu*, and James Cheng. Generalized Higher-Order Tensor Decomposition via Parallel ADMM. In: Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI),  pp.1279-1285,2014. (CCF A)
  • Fanhua Shang, Yuanyuan Liu*, Hanghang Tong, James Cheng, and Hong Cheng. Robust Bilinear Factorization with Missing and Grossly Corrupted Observation. Information Sciences. vol. 370, pp. 53-72, 2015.(IF: 4.305,中科院分区2分区 ).
  • Yuanyuan Liu, Fanhua Shang  , Hong Cheng, James Cheng, and Hanghang Tong. Factor Matrix Trace Norm Minimization for Low-Rank Tensor Completion. In: Proceedings of the 14th SIAM International Conference on Data Mining (SDM), 2014. (CCF B)
  • Yuanyuan Liu, Fanhua Shang, Hong Cheng, and James Cheng. Nuclear Norm Regularized Least Squares Optimization on Grassmannian Manifolds. In: Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI),  pp.515-524,2014. (CCF B)
  • Yuanyua Liu, Licheng Jiao, and Fanhua Shang. An Efficient Matrix Factorization Based Low-Rank Representation for Subspace Clustering. Pattern Recognition, vol. 46, no.1, pp. 284-292, 2013.(IF: 7.197,中科院分区2分区 ).
  • Yuanyuan Liu, Licheng Jiao, and Fanhua Shang. A Fast Tri-Factorization Method for Low-Rank Matrix Representation for Subspace Clustering. Pattern Recognition. vol. 46, no. 1, pp. 284-292, 2013.(IF: 3.926,中科院分区2分区 ).
  • Yuanyuan Liu, Licheng Jiao, and Fanhua Shang. An Efficient Matrix Bi-Factorization Alternative Optimization Method for Trace Norm Minimization. Neural Networkds, vol. 48, pp. 8-18, 2013. (IF: 3.926,中科院分区2分区 ).
  • Yuanyuan Liu, and Fanhua Shang. An Efficient Matrix Factorization Method for Tensor Completion. IEEE Signal Process. Lett.20(4), 307-310, 2013.(IF: 2.813).
  • Fanhua Shang,Yuanyuan Liu, and Fei Wang. Learning Spectral Embedding for Semi-Supervised Clustering. In: Proceedings of the 11th IEEE International Conference on Data Mining (ICDM), 2011. (CCF B).
  • Fanhua Shang, Licheng Jiao, Yuanyuan Liu, and Hanghang Tong. Semi-Supervised Learning with Nuclear Norm Regularization. Pattern Recognition2013. IF: 3.926, 中科院分区2分区) .
  • Licheng Jiao,Fanhua Shang, Fei Wang, and Yuanyuan Liu. Fast Semi-Supervised Clustering with Enhanced Spectral Embedding. Pattern Recognition2012. IF: 3.926,中科院分区2分区) .

 

 

 

     

     

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