We propose a method for sequential Bayesian kernel regression. As is the case for the popular Relevance Vector Machine (RVM) [10, 11], the method automatically identifies the num...
Approaches to text processing that rely on parsing the text with a context-free grammar tend to be slow and error-prone because of the massive ambiguity of long sentences. In cont...
Douglas E. Appelt, Jerry R. Hobbs, John Bear, Davi...
Abstract. We consider a continuous-time model for inventory management with Markov modulated non-stationary demands. We introduce active learning by assuming that the state of the ...
Whether a given nonlinear solver can reach a feasible point for a set of nonlinear constraints depends heavily on the initial point provided. We develop a range of computationally...
Gossip algorithms for aggregation have recently received significant attention for sensor network applications because of their simplicity and robustness in noisy and uncertain en...
Alexandros G. Dimakis, Anand D. Sarwate, Martin J....