Name
Abstract | ||
|---|---|---|
Since the seminal paper by E.M. Gold [Gol67] the computational learning theory community has been presuming that the main problem in the learning theory on the recursion-theoretical level is to restore a grammar from samples of language or a program from its sample computations. However scientists in physics and biology have become accustomed to looking for interesting assertions rather than for a universal theory explaining everything. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1007/3-540-62685-9_23 | EuroCOLT |
Keywords | Field | DocType |
elementary facts,learning formulae,learning theory,computational learning theory | Inductive reasoning,Algorithmic learning theory,Computer science,Learning theory,Grammar,Mathematics education,Computational learning theory,Reinforcement learning,Sample exclusion dimension | Conference |
ISBN | Citations | PageRank |
3-540-62685-9 | 4 | 0.49 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Janis Barzdins | 1 | 199 | 35.69 |
| Rusins Freivalds | 2 | 781 | 90.68 |
| Carl H. Smith | 3 | 194 | 33.15 |