Name
Abstract | ||
|---|---|---|
kProbLog is a simple algebraic extension of Prolog with facts and rules annotated with semiring labels. We propose kProbLog as a language for learning with kernels. kProbLog allows to elegantly specify systems of algebraic expressions on databases. We propose some code examples of gradually increasing complexity, we give a declarative specification of some matrix operations and an algorithm to solve linear systems. Finally we show the encodings of state-of-the-art graph kernels such as Weisfeiler-Lehman graph kernels, propagation kernels and an instance of Graph Invariant Kernels (GIKs), a recent framework for graph kernels with continuous attributes. The number of feature extraction schemas, that we can compactly specify in kProbLog, shows its potential for machine learning applications. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-40566-7_11 | INDUCTIVE LOGIC PROGRAMMING, ILP 2015 |
Keywords | Field | DocType |
Graph kernels, Prolog, Machine learning | Kernel (linear algebra),Algebraic number,Graph property,Computer science,Constraint programming,Theoretical computer science,Prolog,Algebraic extension,Artificial intelligence,Algebraic expression,Machine learning,Semiring | Conference |
Volume | ISSN | Citations |
9575 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francesco Orsini | 1 | 16 | 5.82 |
| Paolo Frasconi | 2 | 2984 | 368.70 |
| Luc De Raedt | 3 | 5481 | 505.49 |