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CDC
2010
IEEE
106views Control Systems» more  CDC 2010»
13 years 4 months ago
Observational learning in an uncertain world
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...
TIT
2002
125views more  TIT 2002»
13 years 9 months ago
Optimal bi-level quantization of i.i.d. sensor observations for binary hypothesis testing
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...
Qian Zhang, Pramod K. Varshney, Richard D. Wesel
TSP
2010
13 years 4 months ago
Joint detection and estimation of multiple objects from image observations
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...
AAAI
2008
14 years 4 days ago
Studies in Solution Sampling
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...
Vibhav Gogate, Rina Dechter
CORR
2007
Springer
112views Education» more  CORR 2007»
13 years 9 months ago
Learning from compressed observations
— 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...
Maxim Raginsky