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CVPR
1997
IEEE
16 years 3 months ago
Global Training of Document Processing Systems Using Graph Transformer Networks
We propose a new machine learning paradigm called Graph Transformer Networks that extends the applicability of gradient-based learning algorithms to systems composed of modules th...
Léon Bottou, Yoshua Bengio, Yann LeCun
MPC
2004
Springer
116views Mathematics» more  MPC 2004»
15 years 7 months ago
An Injective Language for Reversible Computation
Abstract. Erasure of information incurs an increase in entropy and dissipates heat. Therefore, information-preserving computation is essential for constructing computers that use e...
Shin-Cheng Mu, Zhenjiang Hu, Masato Takeichi
ECML
2006
Springer
15 years 5 months ago
An Efficient Approximation to Lookahead in Relational Learners
Abstract. Greedy machine learning algorithms suffer from shortsightedness, potentially returning suboptimal models due to limited exploration of the search space. Greedy search mis...
Jan Struyf, Jesse Davis, C. David Page Jr.
ILP
2007
Springer
15 years 7 months ago
Learning with Kernels and Logical Representations
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...
Paolo Frasconi
IJCAI
2007
15 years 3 months ago
Kernel Conjugate Gradient for Fast Kernel Machines
We propose a novel variant of the conjugate gradient algorithm, Kernel Conjugate Gradient (KCG), designed to speed up learning for kernel machines with differentiable loss functio...
Nathan D. Ratliff, J. Andrew Bagnell