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ASPDAC
2008
ACM
174views Hardware» more  ASPDAC 2008»
13 years 9 months ago
Chebyshev Affine Arithmetic based parametric yield prediction under limited descriptions of uncertainty
In modern circuit design, it is difficult to provide reliable parametric yield prediction since the real distribution of process data is hard to measure. Most existing approaches ...
Jin Sun, Yue Huang, Jun Li, Janet Meiling Wang
NIPS
2007
13 years 8 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
NIPS
2003
13 years 8 months ago
Locality Preserving Projections
Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality Preserving Projections (LPP). These are linear projecti...
Xiaofei He, Partha Niyogi
WAE
1998
118views Algorithms» more  WAE 1998»
13 years 8 months ago
Guarding Scenes against Invasive Hypercubes
In recent years realistic input models for geometric algorithms have been studied. The most important models introduced are fatness, low density, unclutteredness, and small simple...
Mark de Berg, Haggai David, Matthew J. Katz, Mark ...
CEC
2010
IEEE
13 years 8 months ago
Evolvable mechanics: Hardware tools for evolutionary robotics
Embodying robot morphologies evolved in simulation can present serious problems for an engineer when translating simplified simulated mechanisms into working devices, often drawing...
Bill Bigge Inman, R. Harvey