The process of extracting useful knowledge from large datasets has become one of the most pressing problems in today’s society. The problem spans entire sectors, from scientists...
Real-world relational data are seldom stationary, yet traditional collaborative filtering algorithms generally rely on this assumption. Motivated by our sales prediction problem, ...
Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff Schneide...
In constrained clustering it is common to model the pairwise constraints as edges on the graph of observations. Using results from graph theory, we analyze such constraint graphs ...
Sequence segmentation is a central problem in the analysis of sequential and time-series data. In this paper we introduce and we study a novel variation to the segmentation proble...
In this paper, we introduce a simple but efficient greedy algorithm, called SINCO, for the Sparse INverse COvariance selection problem, which is equivalent to learning a sparse Ga...