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» Learning and Inference with Constraints
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PAMI
2011
15 years 1 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
ICML
2005
IEEE
16 years 7 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
CDC
2008
IEEE
171views Control Systems» more  CDC 2008»
16 years 1 months ago
Constrained optimal control theory for differential linear repetitive processes
Abstract. Differential repetitive processes are a distinct class of continuous-discrete twodimensional linear systems of both systems theoretic and applications interest. These pr...
Michael Dymkov, Eric Rogers, Siarhei Dymkou, Krzys...
JSAT
2006
88views more  JSAT 2006»
15 years 6 months ago
On Using Cutting Planes in Pseudo-Boolean Optimization
Cutting planes are a well-known, widely used, and very effective technique for Integer Linear Programming (ILP). However, cutting plane techniques are seldom used in PseudoBoolean...
Vasco M. Manquinho, João P. Marques Silva
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
16 years 7 days ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali