327 search results - page 14 / 66 » A Spectral Approach to Learning Structural Variations in Gra... |
ICALP
1990
Springer
13 years 11 months ago
1990
Springer
Any tree can be represented in a max/ma//y compact form as a directed acyclic graph where common subtrees are factored and shared, being represented only once. Such a compaction ca...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Recent work has shown that one can learn the structure of Gaussian Graphical Models by imposing an L1 penalty on the precision matrix, and then using efficient convex optimization...
ASPDAC
2010
ACM
13 years 5 months ago
2010
ACM
Level-sensitive transparent latches are widely used in high-performance sequential circuit designs. Under process variations, the timing of a transparently latched circuit will ada...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
This paper investigates compression of 3D objects in computer graphics using manifold learning. Spectral compression uses the eigenvectors of the graph Laplacian of an object'...
RECOMB
2004
Springer
14 years 7 months ago
2004
Springer
Nuclear magnetic resonance (NMR) spectroscopy allows scientists to study protein structure, dynamics and interactions in solution. A necessary first step for such applications is ...