We present an integrated approach aimed at predicting layout area needed to implement a behavioral description for a given performance goal. Our approach is novel because: (1) it ...
Seong Yong Ohm, Fadi J. Kurdahi, Nikil Dutt, Min X...
We consider the estimation of a sparse parameter vector from measurements corrupted by white Gaussian noise. Our focus is on unbiased estimation as a setting under which the dif...
Alexander Jung, Zvika Ben-Haim, Franz Hlawatsch, Y...
Managing uncertain data using probabilistic frameworks has attracted much interest lately in the database literature, and a central computational challenge is probabilistic infere...
We present an experiment comparing double exponential smoothing and Kalman filter-based predictive tracking algorithms with derivative free measurement models. Our results show t...
Student modeling is a widely used approach to make inference about a student's attributes like knowledge, learning, etc. If we wish to use these models to analyze and better u...