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VL
1998
IEEE
134views Visual Languages» more  VL 1998»
15 years 2 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»
14 years 10 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
15 years 11 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
15 years 10 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
15 years 10 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...