Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
By attempting to simultaneously partition both the rows (examples) and columns (features) of a data matrix, Co-clustering algorithms often demonstrate surprisingly impressive perf...
Vikas Sindhwani, Jianying Hu, Aleksandra Mojsilovi...
- Two software packages for solving sparse systems of linear equations, SuperLU and UMFPACK, have been integrated with the University of Maine Ice Sheet Model for predicting the fo...
Abstract. Finite element mesh adaptation methods can be used to improve the efficiency and accuracy of solutions to computational modeling problems. In many applications involving ...
Adam C. Woodbury, Jason F. Shepherd, Matthew L. St...
Co-clustering is the simultaneous partitioning of the rows and columns of a matrix such that the blocks induced by the row/column partitions are good clusters. Motivated by severa...
Aris Anagnostopoulos, Anirban Dasgupta, Ravi Kumar