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SIGIR
2009
ACM
13 years 11 months ago
Approximating true relevance distribution from a mixture model based on irrelevance data
Pseudo relevance feedback (PRF), which has been widely applied in IR, aims to derive a distribution from the top n pseudo relevant documents D. However, these documents are often ...
Peng Zhang, Yuexian Hou, Dawei Song
ICML
2005
IEEE
14 years 5 months ago
Compact approximations to Bayesian predictive distributions
We provide a general framework for learning precise, compact, and fast representations of the Bayesian predictive distribution for a model. This framework is based on minimizing t...
Edward Snelson, Zoubin Ghahramani
ICML
2005
IEEE
14 years 5 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
ICMCS
2006
IEEE
174views Multimedia» more  ICMCS 2006»
13 years 10 months ago
Web Image Mining Based on Modeling Concept-Sensitive Salient Regions
In this paper, we propose a probabilistic model for web image mining, which is based on concept-sensitive salient regions without human intervene. Our goal is to achieve a middle-...
Jing Liu, Qingshan Liu, Jinqiao Wang, Hanqing Lu, ...
ATAL
2007
Springer
13 years 8 months ago
Confidence-based policy learning from demonstration using Gaussian mixture models
We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
Sonia Chernova, Manuela M. Veloso