We study a model of observational learning in social networks in the presence of uncertainty about agents' type distributions. Each individual receives a private noisy signal ...
Daron Acemoglu, Munther A. Dahleh, Asuman E. Ozdag...
We consider the problem of binary hypothesis testing using binary decisions from independent and identically distributed (i.i.d). sensors. Identical likelihood-ratio quantizers wit...
The problem of jointly detecting multiple objects and estimating their states from image observations is formulated in a Bayesian framework by modeling the collection of states as ...
Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Sute...
We introduce novel algorithms for generating random solutions from a uniform distribution over the solutions of a boolean satisfiability problem. Our algorithms operate in two pha...
— The problem of statistical learning is to construct a predictor of a random variable Y as a function of a related random variable X on the basis of an i.i.d. training sample fr...