Approximate Inference in Collective Graphical Models

• المؤلفون الرئيسيون: SHELDON, Daniel, SUN, Tao, KUMAR, Akshat, DIETTERICH, Thomas G.
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2013
• الموضوعات: Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/2199; https://ink.library.smu.edu.sg/context/sis_research/article/3199/viewcontent/sheldon13.pdf
• المؤسسة: Singapore Management University

We study the problem of approximate inference in collective graphical models (CGMs), which were recently introduced to model the problem of learning and inference with noisy aggregate observations. We first analyze the complexity of inference in CGMs: unlike inference in conventional graphical model...