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ICML
2006
IEEE
16 years 7 months ago
Bayesian regression with input noise for high dimensional data
This paper examines high dimensional regression with noise-contaminated input and output data. Goals of such learning problems include optimal prediction with noiseless query poin...
Jo-Anne Ting, Aaron D'Souza, Stefan Schaal
VMCAI
2009
Springer
16 years 1 months ago
LTL Generalized Model Checking Revisited
Given a 3-valued abstraction of a program (possibly generated using rogram analysis and predicate abstraction) and a temporal logic formula, generalized model checking (GMC) checks...
Patrice Godefroid, Nir Piterman
ASPDAC
2009
ACM
164views Hardware» more  ASPDAC 2009»
16 years 1 months ago
Accounting for non-linear dependence using function driven component analysis
Majority of practical multivariate statistical analyses and optimizations model interdependence among random variables in terms of the linear correlation among them. Though linear...
Lerong Cheng, Puneet Gupta, Lei He
ACMACE
2007
ACM
15 years 10 months ago
Application of dimensionality reduction techniques to HRTFS for interactive virtual environments
Fundamental to the generation of 3D audio is the HRTF processing of acoustical signals. Unfortunately, given the high dimensionality of HRTFs, incorporating them into dynamic/inte...
Bill Kapralos, Nathan Mekuz
DAC
2005
ACM
15 years 8 months ago
Total power reduction in CMOS circuits via gate sizing and multiple threshold voltages
Minimizing power consumption is one of the most important objectives in IC design. Resizing gates and assigning different Vt’s are common ways to meet power and timing budgets. ...
Feng Gao, John P. Hayes