A key challenge in recommender system research is how to effectively profile new users, a problem generally known as cold-start recommendation. Recently the idea of progressivel...
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Abstract. Starting from existing spreadsheet software, like Lotus 1-23R , ExcelR , or Spreadsheet 2000R , we propose a sequence of enhancements to fully integrate constraint-based ...
This paper studies the effects of training data on binary text classification and postulates that negative training data is not needed and may even be harmful for the task. Tradit...
In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is m...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...