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» Learning Mixtures of DAG Models
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CVPR
2009
IEEE
15 years 5 months ago
Epitomized Priors for Multi-labeling Problems
Image parsing remains difficult due to the need to combine local and contextual information when labeling a scene. We approach this problem by using the epitome as a prior over ...
Jonathan Warrell, Simon J. D. Prince, Alastair P. ...
KDD
2005
ACM
112views Data Mining» more  KDD 2005»
14 years 10 months ago
Model-based overlapping clustering
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Arindam Banerjee, Chase Krumpelman, Joydeep Ghosh,...
MLG
2007
Springer
14 years 4 months ago
Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, Jose Santos
NIPS
2008
13 years 11 months ago
Learning the Semantic Correlation: An Alternative Way to Gain from Unlabeled Text
In this paper, we address the question of what kind of knowledge is generally transferable from unlabeled text. We suggest and analyze the semantic correlation of words as a gener...
Yi Zhang 0010, Jeff Schneider, Artur Dubrawski
SEAL
2010
Springer
13 years 7 months ago
Dominance-Based Pareto-Surrogate for Multi-Objective Optimization
Abstract. Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Paret...
Ilya Loshchilov, Marc Schoenauer, Michèle S...