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VL
1998
IEEE
134views Visual Languages» more  VL 1998»
15 years 6 months ago
Visual Semantics - Or: What You See is What You Compute
We introduce visual graphs as an intermediate repren between concrete visual syntax and abstract graph syntax. In a visual graph some nodes are shown as geometric figures, and som...
Martin Erwig
FPGA
2010
ACM
232views FPGA» more  FPGA 2010»
15 years 2 months ago
High-throughput bayesian computing machine with reconfigurable hardware
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Mingjie Lin, Ilia Lebedev, John Wawrzynek
CVPR
1997
IEEE
16 years 4 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
ICML
2009
IEEE
16 years 2 months ago
Learning spectral graph transformations for link prediction
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Andreas Lommatzsch, Jérôme Kunegis
ICML
2005
IEEE
16 years 2 months ago
Learning from labeled and unlabeled data on a directed graph
We propose a general framework for learning from labeled and unlabeled data on a directed graph in which the structure of the graph including the directionality of the edges is co...
Bernhard Schölkopf, Dengyong Zhou, Jiayuan Hu...