Kishan Wimalawarne


We have preprints which we can provide on request.


  • Kishan Wimalawarne, Makoto Yamada, and Hiroshi Mamitsuka, "Scaled Coupled Norms and Coupled Higher Order Tensor Completion" (Accepted to Neural Computation)
  • Kishan Wimalawarne, Hiroshi Mamitsuka, Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms, NeurIPS 2018 Link, code


  • Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka, Convex Coupled Matrix and Tensor Completion, Neural Computation, August 2018 0:0, Pages 1-33, Preprint,code


  • Makoto Yamada, Wenzhao Lian, Amit Goyal, Jianhui Chen, Kishan Wimalawarne, Suleiman A Khan, Samuel Kaski, Hiroshi Mamitsuka, Yi Chang, Convex Factorization Machine for Regression. KDD 17 Link


  • Kishan Wimalawarne, Ryota Tomioka, and Masashi Sugiyama, Theoretical and Experimental Analyses of Tensor-Based Regression and Classification, Neural Computation, April 2016, Vol. 28, No. 4, Pages 686-715. Link, (Preprint) code


  • Wimalawarne, K., Sugiyama, M., & Tomioka, R.  Multitask learning meets tensor factorization: Task imputation via convex optimization.  In Z. Ghahramani, M. Welling, C. Cortes, N. D. Lawrence, and K. Q. Weinberger (Eds.), Advances in Neural Information Processing Systems 27, pp.2825-2833, 2014. (Presented at Neural Information Processing Systems (NeurIPS 2014 [former NIPS]), Montreal, Quebec, Canada, Dec. 8-11, 2014) Link code