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JMLR
2010
134views more  JMLR 2010»
13 years 2 months ago
Inference of Graphical Causal Models: Representing the Meaningful Information of Probability Distributions
This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Jan Lemeire, Kris Steenhaut
IASSE
2004
13 years 9 months ago
A Model for Multi-relational Data Mining on Demand Forecasting
Accurate demand forecasting remains difficult and challenging in today's competitive and dynamic business environment, but even a little improvement in demand prediction may ...
Qin Ding, Bhavin Parikh
COLING
2008
13 years 9 months ago
Exact Inference for Multi-label Classification using Sparse Graphical Models
This paper describes a parameter estimation method for multi-label classification that does not rely on approximate inference. It is known that multi-label classification involvin...
Yusuke Miyao, Jun-ichi Tsujii
JMLR
2010
158views more  JMLR 2010»
13 years 2 months ago
Topology Selection in Graphical Models of Autoregressive Processes
An algorithm is presented for topology selection in graphical models of autoregressive Gaussian time series. The graph topology of the model represents the sparsity pattern of the...
Jitkomut Songsiri, Lieven Vandenberghe
INFORMATICALT
2002
91views more  INFORMATICALT 2002»
13 years 7 months ago
Quantitative Forecasting and Assessment Models in the State Education System
This paper presents model-based forecasting of the Lithuanian education system in the period of 2001
Vydunas Saltenis, Gintautas Dzemyda, Vytautas Ties...