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CDC
2010
IEEE
106views Control Systems» more  CDC 2010»
14 years 6 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...
AAAI
2011
13 years 11 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
SBP
2012
Springer
13 years 7 months ago
Addiction Dynamics May Explain the Slow Decline of Smoking Prevalence
The prevalence of cigarette smoking in the United States has declined very slowly over the last four decades, despite much effort by multiple governmental and non-governmental ins...
Gaurav Tuli, Madhav V. Marathe, S. S. Ravi, Samart...
SDM
2012
SIAM
294views Data Mining» more  SDM 2012»
13 years 2 months ago
Kernelized Probabilistic Matrix Factorization: Exploiting Graphs and Side Information
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
Tinghui Zhou, Hanhuai Shan, Arindam Banerjee, Guil...
IBMRD
2011
112views more  IBMRD 2011»
14 years 6 months ago
Sensor Andrew: Large-scale campus-wide sensing and actuation
—We present Sensor Andrew, a multi-disciplinary campus-wide scalable sensor network that is designed to host a wide range of sensor, actuator and low-power applications. The goal...
Anthony Rowe, Mario Berges, Gaurav Bhatia, Ethan G...