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» Structured Learning with Approximate Inference
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UAI
2008
14 years 11 months ago
Bayesian Out-Trees
A Bayesian treatment of latent directed graph structure for non-iid data is provided where each child datum is sampled with a directed conditional dependence on a single unknown p...
Tony Jebara
UAI
1996
14 years 11 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
SDM
2009
SIAM
162views Data Mining» more  SDM 2009»
15 years 7 months ago
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction.
We propose Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using aux...
Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanish...
EGICE
2006
15 years 1 months ago
Evolutionary Generation of Implicative Fuzzy Rules for Design Knowledge Representation
Abstract. In knowledge representation by fuzzy rule based systems two reasoning mechanisms can be distinguished: conjunction-based and implication-based inference. Both approaches ...
Mark Freischlad, Martina Schnellenbach-Held, Torbe...
JMLR
2010
119views more  JMLR 2010»
14 years 4 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun