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» On Tree-Constrained Matchings and Generalizations
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JSC
2008
72views more  JSC 2008»
14 years 9 months ago
Flat matching
Abstract. Flat theory with sequence variables and flexible arity symbols has infinitary matching and unification type. Decidability of general unification is shown and a unificatio...
Temur Kutsia
ACL
2008
14 years 11 months ago
Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields
This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accompli...
Gideon S. Mann, Andrew McCallum
IPCO
1998
87views Optimization» more  IPCO 1998»
14 years 11 months ago
Simple Generalized Maximum Flow Algorithms
We introduce a gain-scaling technique for the generalized maximum ow problem. Using this technique, we present three simple and intuitive polynomial-time combinatorialalgorithms fo...
Éva Tardos, Kevin D. Wayne
DISOPT
2010
132views more  DISOPT 2010»
14 years 9 months ago
General approximation schemes for min-max (regret) versions of some (pseudo-)polynomial problems
While the complexity of min-max and min-max regret versions of most classical combinatorial optimization problems has been thoroughly investigated, there are very few studies abou...
Hassene Aissi, Cristina Bazgan, Daniel Vanderpoote...
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JMLR
2010
153views more  JMLR 2010»
14 years 4 months ago
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data
In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits m...
Gideon S. Mann, Andrew McCallum