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» A Graph Based Data Model for Graphics Interpretation
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ICCS
2004
Springer
15 years 8 months ago
Clustering of Conceptual Graphs with Sparse Data
This paper gives a theoretical framework for clustering a set of conceptual graphs characterized by sparse descriptions. The formed clusters are named in an intelligible manner thr...
Jean-Gabriel Ganascia, Julien Velcin
JMLR
2006
118views more  JMLR 2006»
15 years 3 months ago
Learning Factor Graphs in Polynomial Time and Sample Complexity
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
Pieter Abbeel, Daphne Koller, Andrew Y. Ng
CORR
2010
Springer
137views Education» more  CORR 2010»
15 years 3 months ago
Open Graphs and Monoidal Theories
String diagrams are a powerful tool for reasoning about physical processes, logic circuits, tensor networks, and many other compositional structures. The distinguishing feature of...
Lucas Dixon, Aleks Kissinger
PG
1997
IEEE
15 years 7 months ago
3D geometric metamorphosis based on harmonic map
Recently, animations with deforming objects are frequently used in various Computer Graphics applications. Metamorphosis (or morphing) of three dimensional objects is one of techn...
Takashi Kanai, Hiromasa Suzuki, Fumihiko Kimura
SODA
2001
ACM
79views Algorithms» more  SODA 2001»
15 years 4 months ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro