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» Teaching Regression with Simulation
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CSDA
2006
145views more  CSDA 2006»
13 years 7 months ago
Improved predictions penalizing both slope and curvature in additive models
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...
Magne Aldrin
IV
2007
IEEE
366views Visualization» more  IV 2007»
14 years 1 months ago
Algorithm Visualization in Teaching Spatial Data Algorithms
Algorithm visualization is a widely–used tool for teaching data structures and algorithms. Spatial data algorithms are algorithms that are designed to process multidimensional d...
Jussi Nikander, Juha Helminen
MICRO
2008
IEEE
153views Hardware» more  MICRO 2008»
14 years 2 months ago
CPR: Composable performance regression for scalable multiprocessor models
Uniprocessor simulators track resource utilization cycle by cycle to estimate performance. Multiprocessor simulators, however, must account for synchronization events that increas...
Benjamin C. Lee, Jamison D. Collins, Hong Wang 000...
SIGCSE
2002
ACM
192views Education» more  SIGCSE 2002»
13 years 7 months ago
A new instructional operating system
This paper presents a new instructional operating system, OS/161, and simulated execution environment, System/161, for use in teaching an introductory undergraduate operating syst...
David A. Holland, Ada T. Lim, Margo I. Seltzer
APSEC
2005
IEEE
14 years 1 months ago
Simulation-based Validation and Defect Localization for Evolving, Semi-Formal Requirements Models
When requirements models are developed in an iterative and evolutionary way, requirements validation becomes a major problem. In order to detect and fix problems early, the speci...
Christian Seybold, Silvio Meier