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» Selectivity Estimation using Probabilistic Models
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ICML
2005
IEEE
16 years 5 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
CIKM
2011
Springer
14 years 4 months ago
Hybrid models for future event prediction
We present a hybrid method to turn off-the-shelf information retrieval (IR) systems into future event predictors. Given a query, a time series model is trained on the publication...
Giuseppe Amodeo, Roi Blanco, Ulf Brefeld
RSS
2007
159views Robotics» more  RSS 2007»
15 years 6 months ago
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
Christian Plagemann, Kristian Kersting, Patrick Pf...
156
Voted
ML
2000
ACM
157views Machine Learning» more  ML 2000»
15 years 4 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
ECIR
2008
Springer
15 years 6 months ago
Utilizing Passage-Based Language Models for Document Retrieval
Abstract. We show that several previously proposed passage-based document ranking principles, along with some new ones, can be derived from the same probabilistic model. We use lan...
Michael Bendersky, Oren Kurland