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PAMI
2011
13 years 2 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
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
14 years 1 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
ICDM
2010
IEEE
154views Data Mining» more  ICDM 2010»
13 years 5 months ago
Discrimination Aware Decision Tree Learning
Abstract--Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute , find a classifier with high predictive accu...
Faisal Kamiran, Toon Calders, Mykola Pechenizkiy
NIPS
2004
13 years 9 months ago
The Power of Selective Memory: Self-Bounded Learning of Prediction Suffix Trees
Prediction suffix trees (PST) provide a popular and effective tool for tasks such as compression, classification, and language modeling. In this paper we take a decision theoretic...
Ofer Dekel, Shai Shalev-Shwartz, Yoram Singer
CORR
2008
Springer
108views Education» more  CORR 2008»
13 years 7 months ago
Resolution Trees with Lemmas: Resolution Refinements that Characterize DLL Algorithms with Clause Learning
Resolution refinements called w-resolution trees with lemmas (WRTL) and with input lemmas (WRTI) are introduced. Dag-like resolution is equivalent to both WRTL and WRTI when there...
Samuel R. Buss, Jan Hoffmann 0002, Jan Johannsen