Name
Abstract | ||
|---|---|---|
Proposed and implemented is the language CoReJava (constraint optimization regression in Java), which extends the programming language Java with regression analysis, i.e., the capability to do parameter estimation for a function. CoReJava is unique in that functional forms for regression analysis are expressed as first-class citizens, i.e., as Java programs, in which some parameters are not a priori known, but need to be learned from training sets provided as input. Typical applications of CoReJava include calibration of parameters of computational processes, described as OO programs. To implement regression learning, the CoReJava compiler (1) analyses the structure of the parameterized Java program that represent a functional form, (2) automatically generates a constraint optimization problem, in which constraint variables are the unknown parameters, and the objective function to be minimized is the sum of squares of errors w.r.t. the training set, and (3) solves the optimization problem using an external non-linear optimization solver. CoReJava then executes as a regular Java program, in which the initially unknown parameters are replaced with the found optimal values. CoReJava syntax and semantics are formally defined and exemplified using a simple supply chain example. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICMLA.2008.144 | San Diego, CA |
Keywords | Field | DocType |
time-series segmentation,bayesian approach,object-oriented programs,unsupervised scenario,linear gaussian,fundamental problem,segmentation model,functional form,optimization problem,sum of squares,materials,object oriented programming,supply chain,programming language,optimization,java,objective function,constraint optimization,supply chains,regression analysis,parameter estimation | Programming language,Computer science,Theoretical computer science,Artificial intelligence,Optimization problem,Parameterized complexity,Object-oriented programming,Compiler,Solver,Explained sum of squares,Java,Machine learning,Constrained optimization | Conference |
ISBN | Citations | PageRank |
978-0-7695-3495-4 | 8 | 1.02 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Brodsky | 1 | 510 | 92.99 |
| Juan Luo | 2 | 11 | 2.16 |
| Hadon Nash | 3 | 38 | 4.56 |