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NIPS
2007
13 years 11 months ago
Compressed Regression
Recent research has studied the role of sparsity in high dimensional regression and signal reconstruction, establishing theoretical limits for recovering sparse models from sparse...
Shuheng Zhou, John D. Lafferty, Larry A. Wasserman
AICCSA
2001
IEEE
172views Hardware» more  AICCSA 2001»
14 years 1 months ago
Methods and Metrics for Selective Regression Testing
In corrective maintenance, selective regression testing includes test selection from previously run test suite and test coverage identification. We propose three reductionbased re...
Rami Bahsoon, Nashat Mansour
UAI
2008
13 years 11 months ago
Learning Hidden Markov Models for Regression using Path Aggregation
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Keith Noto, Mark Craven
CSDA
2006
71views more  CSDA 2006»
13 years 9 months ago
Computation of Huber's M-estimates for a block-angular regression problem
Huber's M-estimation technique is applied to a block-angular regression problem, which may arise from some applications. A recursive, modified Newton approach to computing th...
Xiao-Wen Chang
GECCO
2008
Springer
133views Optimization» more  GECCO 2008»
13 years 11 months ago
Using feature-based fitness evaluation in symbolic regression with added noise
Symbolic regression is a popular genetic programming (GP) application. Typically, the fitness function for this task is based on a sum-of-errors, involving the values of the depe...
Janine H. Imada, Brian J. Ross