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Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs.

by Rajeev H Dehejia , Sadek Wahba - Journal of the American Statistical Association, , 1999
"... ..."
Abstract - Cited by 733 (5 self) - Add to MetaCart
Abstract not found

Estimating the effect of training programs on earnings.

by Orley Ashenfelter - Review of Economics and Statistics , 1978
"... ..."
Abstract - Cited by 359 (1 self) - Add to MetaCart
Abstract not found

Evaluating the Econometric Evaluations of Training Programs With Experimental Data," Industrial Relations Section, Working Paper No.

by Robert J Lalonde , 1984
"... ..."
Abstract - Cited by 553 (5 self) - Add to MetaCart
Abstract not found

Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs

by Orley Ashenfelter, David Card - Review of Economics and Statistics , 1985
"... In this paper we set out some methods that utilize the longitudinal structure of earnings of trainees and a comparison group to estimate the effectiveness of training for the 1976 cohort of CETA trainees. By fitting a components-of-variance model of earnings to the control group, and by posing a sim ..."
Abstract - Cited by 302 (8 self) - Add to MetaCart
simple model of program participation, we are able to predict the entire pre-training and post-training earnings histories of the trainees. The fit of these predictions to the pre-training earnings of the CETA participants provides a test of the model of earnings generation and program participation

Training Support Vector Machines: an Application to Face Detection

by Edgar Osuna, Robert Freund, Federico Girosi , 1997
"... We investigate the application of Support Vector Machines (SVMs) in computer vision. SVM is a learning technique developed by V. Vapnik and his team (AT&T Bell Labs.) that can be seen as a new method for training polynomial, neural network, or Radial Basis Functions classifiers. The decision sur ..."
Abstract - Cited by 727 (1 self) - Add to MetaCart
We investigate the application of Support Vector Machines (SVMs) in computer vision. SVM is a learning technique developed by V. Vapnik and his team (AT&T Bell Labs.) that can be seen as a new method for training polynomial, neural network, or Radial Basis Functions classifiers. The decision

Training Programs? by

by Centre For, Forest Worker, Tom Nesbit, Jane Dawson
"... Research on Work and ..."
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Research on Work and

Enhancing medication adherence: Clinician outcomes from the Medication Alliance training program

by Mitchell K. Byrne, Frank P. Deane, Gordon Lambert, Tim Coombs - Australian & New Zealand Journal of Psychiatry , 2004
"... training program ..."
Abstract - Cited by 2 (0 self) - Add to MetaCart
training program

Making Large-Scale Support Vector Machine Learning Practical

by Thorsten Joachims , 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract - Cited by 628 (1 self) - Add to MetaCart
learning tasks with many training examples, off-the-shelf optimization techniques for general quadratic programs quickly become intractable in their memory and time requirements. SVM light1 is an implementation of an SVM learner which addresses the problem of large tasks. This chapter presents

Making Large-Scale SVM Learning Practical

by Thorsten Joachims , 1998
"... Training a support vector machine (SVM) leads to a quadratic optimization problem with bound constraints and one linear equality constraint. Despite the fact that this type of problem is well understood, there are many issues to be considered in designing an SVM learner. In particular, for large lea ..."
Abstract - Cited by 1861 (17 self) - Add to MetaCart
learning tasks with many training examples, off-the-shelf optimization techniques for general quadratic programs quickly become intractable in their memory and time requirements. SV M light1 is an implementation of an SVM learner which addresses the problem of large tasks. This chapter presents algorithmic

Planning a Training Program

by Mary Ann Liebert, B. H. Ewald
"... The: Public Health Service and the USDA now require animal welfare training programs. In planning an animal welfare training program, three questions must be answered: Who? What? and How? An analysis of the groups and individuals required to partici-pate can provide information for eventual course d ..."
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The: Public Health Service and the USDA now require animal welfare training programs. In planning an animal welfare training program, three questions must be answered: Who? What? and How? An analysis of the groups and individuals required to partici-pate can provide information for eventual course
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