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JMLR
2006
186views more  JMLR 2006»
13 years 7 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
ENTCS
2007
105views more  ENTCS 2007»
13 years 7 months ago
Narrowing and Rewriting Logic: from Foundations to Applications
Narrowing was originally introduced to solve equational E-unification problems. It has also been recognized as a key mechanism to unify functional and logic programming. In both ...
Santiago Escobar, José Meseguer, Prasanna T...
ENTCS
2007
137views more  ENTCS 2007»
13 years 7 months ago
Formal Sequentialization of Distributed Systems via Program Rewriting
Formal sequentialization is introduced as a rewriting process for the reduction of parallelism and internal communication statements of distributed imperative programs. It constru...
Miquel Bertran, Francesc-Xavier Babot, August Clim...
NECO
2008
170views more  NECO 2008»
13 years 7 months ago
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Deep Belief Networks (DBN) are generative neural network models with many layers of hidden explanatory factors, recently introduced by Hinton et al., along with a greedy layer-wis...
Nicolas Le Roux, Yoshua Bengio
GC
2007
Springer
13 years 7 months ago
Precoloring Extension of Co-Meyniel Graphs
The pre-coloring extension problem consists, given a graph G and a set of nodes to which some colors are already assigned, in finding a coloring of G with the minimum number of co...
Vincent Jost, Benjamin Lévêque, Fr&ea...