| 2005 | - | A Bayesian view of language evolution by iterated learning - Griffiths,Kalish | :: | 6 |
| 2003 | - | Iterated Learning: a framework for the emergence of language - Smith,Kirby,Brighton | :: | 34 |
| 2001 | - | Generalization, similarity, and Bayesian inference - Tenenbaum,Griffiths | :: | 4 |
| 2001 | - | Spontaneous evolution of linguistic structure: an iterated learning model of the emergence of regularity and irregularity - Kirby | :: | 96 |
| 2000 | - | Minimization of Boolean complexity in human concept learning - Feldman | :: | 4 |
| 1999 | - | A Bayesian framework for concept learning - Tenenbaum | :: | 3 |
| 1997 | - | Markov Chains - Norris | :: | 6 |
| 1995 | - | The nature of statistical learning theory - Vapnik | :: | 11 |
| 1994 | - | Comparing models of rule-based classification learning: A replication and extension of Shepard - Nosofsky,Gluck,Palmeri,McKinley,Glauthier | :: | 2 |
| 1994 | - | An introduction to computational learning theory - Kearns,Vazirani | :: | 6 |
| 1992 | - | Neural networks and the bias-variance dilemma - Geman,Bienenstock,Doursat | :: | 5 |
| 1977 | - | Maximum likelihood from incomplete data via the EM algorithm - Dempster,Laird,Rubin | :: | 2 |
| 1961 | - | Learning and memorization of classifications - Shepard,Hovland,Jenkins | :: | 2 |
| 1955 | - | Fact, Fiction, and Forecast - Goodman | :: | 3 |