Selecting basis functions to form a regression model for...

Electrical computers and digital processing systems: memory – Storage accessing and control – Hierarchical memories

Reexamination Certificate

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C711S133000, C711S134000, C714S701000, C714S702000, C714S704000, C714S718000, C702S108000, C702S119000, C702S120000

Reexamination Certificate

active

07346736

ABSTRACT:
One embodiment of the present invention provides a system that selects bases to form a regression model for cache performance. During operation, the system receives empirical data for a cache rate. The system also receives derivative constraints for the cache rate. Next, the system obtains candidate bases that satisfy the derivative constraints. For each of these candidate bases, the system: (1) computes an aggregate error E incurred using the candidate basis over the empirical data; (2) computes an instability measure I of an extrapolation fit for using the candidate basis over an extrapolation region; and then (3) computes a selection criterion F for the candidate basis, wherein F is a function of E and I. Finally, the system minimizes the selection criterion F across the candidate bases to select the basis used for the regression model.

REFERENCES:
Gluhovsky, Vengerov and O'Krafka, by Sun Microsystems Laboratories, “Comprehensive Multivariate Extrapolation Modeling of Multiprocessor Cache Miss reates”, Jul. 2006, ACM Journal Name, vol. V.
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Publication entitled: “Feasible Nonparametric Estimation of Multiargument Monotone Functions”, by Hari Mukarjee et al., Journal of the American Statistical Association, vol. 89, No. 425 (Mar. 1994), pp. 77-80.
Publication entitled: Data-Driven Bandwidth Selection in Local Polynomial Fitting: Variable Bandwidth and Spatial Adaptation, by Jianqing Fan et al., Journal of the Royal Statistical Society, Series B (methodological), vol. 57, No. 2 (1995), pp. 371-394.
Publication entitled: “Multiplicative Updates for Nonnegative Quadratic Programming in Support Vector Machines”, by Fei Sha et al., University of Pennsylvania, Advances in Neural Information Processing Systems 15 (NIPS 2002), pp. 1065-1072.

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