We will be reading the following articles:
Andrews, M. & Vigliocco, G. (2010). The Hidden Markov Topic Model. Topics in Cognitive Science, 2, 101-113.
Chater, N., and Manning, C. (2006). Probabilistic models of language processing and acquisition. Trends in Cognitive Sciences, 10(7), 335-344.
Chemla, E., Mintz, T., Bernal, S., and Christophe, A. (2009). Categorizing words using 'frequent frames': what cross-linguistic analyses reveal about distributional acquisition strategies. Developmental Science, 12(3), 396-406.
Christiansen, M., Onnis, L., and Hockema, S. (2009). The secret is in the sound: from unsegmented speech to lexical categories. Developmental Science, 12(3), 388-395.
Dillon, B. & Idsardi, B. (2009). Investigating Statistical Approaches to Building a Phonology. Ms. University of Maryland.
Feldman, N., Griffiths, T., and Morgan, J. (2009). The Influence of Categories on Perception: Explaining the Perceptual Magent Effect as Optimal Statistical Inference. Psychological Review, 116(4), 752-782.
Feldman, N., Griffiths, T., and Morgan, J. (2009). Learning phonetic categories by learning a lexicon. Proceedings of the 31st Annual Conference on Cognitive Science.
Foraker, S., Regier, T., Kheterpal, N., Perfors, A., and Tenenbaum, J. (2009). Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One. Cognitive Science, 33, 287-300.
Frank, M., Goodman, N., & Tenenbaum, J. (2009). Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning. Psychological Science, 20(5), 578-585.
Freudenthal, D., Pine, J., and Gobet, F. (2009). Simulating the Referential Properties of Dutch, German, and English Root Infinitives in MOSAIC. Language Learning and Development, 5(1), 1-29.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian Framework for Word Segmentation: Exploring the Effects of Context. Cognition, 112(1), 21-54.
Griffiths, T., Steyvers, M., & Tenenbaum, J. (2007). Topics in Semantic Representation. Psychological Review, 114(2), 211-244.
Hsu, A. & Griffiths, T. (2009). Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning. Advances in Neural Information Processing Systems 22.
Johnson, K. (2004). Gold's Theorem and Cognitive Science. Philosophy of Science, 71, 571-592.
Kam, X., Stoyneshka, I., Tornyova, L., Fodor, J.D., and Sakas, W. (2008). Bigrams and the Richness of the Stimulus. Cognitive Science, 32(4), 771-787.
Kemp, C., Perfors, A., Tenenbaum, J. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.
Landauer, T.K., & Dumais, S.T. (1997). A solution to Plato's problem: The Latent Semantic Analysis theory of acquisition, induction and representation of knowledge. Psychological Review, 104, 211-240.
McMurray, B. & Hollich, G. (2009). Core computational principals of language acquisition: can statistical learning do the job? Introduction to Special Section. Developmental Science, 12(3), 365-368.
Mintz, T. (2003). Frequent frames as a cue for grammatical categories in child directed speech. Cognition, 90, 91-117.
Navarro, D., Griffiths, T., Steyvers, M., and Lee, M. (2006). Modeling individual differences using Dirichlet processes. Journal of Mathematical Psychology, 50, 101-122.
Pearl, L., Goldwater, S., & Steyvers, M. (2010). How Ideal Are We? Incorporating Human Limitations into Bayesian Models of Word Segmentation. BUCLD 34: Proceedings of the 34th annual Boston University Conference on Child Language Development, Somerville, MA: Cascadilla Press.
Pearl, L. & Lidz, J. (2009). When domain-general learning fails and when it succeeds: Identifying the contribution of domain-specificity. Language Learning & Development, 5(4), 235-265.
Perfors, A., Tenenbaum, J., Gibson, T., and Regier, T. (forthcoming). How recursive is language? A Bayesian exploration. Linguistic Review.
Perfors, A., Tenenbaum, J., & Regier, T. (2006). Poverty of the Stimulus? A Rational Approach. In R. Sun & N. Miyake (eds.) Proceedings of the 28th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society: 663-668.
Perfors, A., Tenenbaum, J., & Regier, T. (under review). The learnability of abstract syntactic principles. Ms.
Reali, F. & Christiansen, M. (2005). Structure Dependence in Language Acquisition: Uncovering the Richness of the Stimulus: Stucture Dependence and Indirect Statistical Evidence, Cognitive Science, 29, 1007-1028.
Regier, T., and Gahl, S. (2004). Learning the unlearnable: the role of missing evidence. Cognition, 93, 147-155.
Samuelson, L. (2009). A core principle of studying language acquisition: it's a developmental system. Developmental Science, 12(3), 407-409.
Shi, L., Griffiths, T. L., Feldman, N. H, & Sanborn, A. N. (in press). Exemplar models as a mechanism for performing Bayesian inference. Psychonomic Bulletin & Review.
Soderstrom, M., Conwell, E., Feldman, N., Morgan, J. (2009). The learner as statistician: three principles of computational success in language acquisition. Developmental Science, 12(3), 409-411.
Steyvers, M. & Griffiths, T. (2007). Probabilistic topic models. In T. Landauer, D. S. McNamara, S. Dennis, & W. Kintsch (Eds.), Handbook of Latent Semantic Analysis. Hillsdale, NJ: Erlbaum.
Udden, J., Araujo, S., Forkstam, C., Ingvar, M., Hagoort, P., & Petersson, K. M. (2009). A matter of time: Implicit acquisition of recursive sequence structures. In N. Taatgen, & H. Van Rijn (Eds.), Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, 2444-2449.
Xu, F., & Tenenbaum, J. (2007). Word Learning as Bayesian Inference, Psychological Review, 114(2), 245-272.
Chater, N., and Manning, C. (2006). Probabilistic models of language processing and acquisition. Trends in Cognitive Sciences, 10(7), 335-344.
Chemla, E., Mintz, T., Bernal, S., and Christophe, A. (2009). Categorizing words using 'frequent frames': what cross-linguistic analyses reveal about distributional acquisition strategies. Developmental Science, 12(3), 396-406.
Christiansen, M., Onnis, L., and Hockema, S. (2009). The secret is in the sound: from unsegmented speech to lexical categories. Developmental Science, 12(3), 388-395.
Dillon, B. & Idsardi, B. (2009). Investigating Statistical Approaches to Building a Phonology. Ms. University of Maryland.
Feldman, N., Griffiths, T., and Morgan, J. (2009). The Influence of Categories on Perception: Explaining the Perceptual Magent Effect as Optimal Statistical Inference. Psychological Review, 116(4), 752-782.
Feldman, N., Griffiths, T., and Morgan, J. (2009). Learning phonetic categories by learning a lexicon. Proceedings of the 31st Annual Conference on Cognitive Science.
Foraker, S., Regier, T., Kheterpal, N., Perfors, A., and Tenenbaum, J. (2009). Indirect Evidence and the Poverty of the Stimulus: The Case of Anaphoric One. Cognitive Science, 33, 287-300.
Frank, M., Goodman, N., & Tenenbaum, J. (2009). Using Speakers' Referential Intentions to Model Early Cross-Situational Word Learning. Psychological Science, 20(5), 578-585.
Freudenthal, D., Pine, J., and Gobet, F. (2009). Simulating the Referential Properties of Dutch, German, and English Root Infinitives in MOSAIC. Language Learning and Development, 5(1), 1-29.
Goldwater, S., Griffiths, T. L., & Johnson, M. (2009). A Bayesian Framework for Word Segmentation: Exploring the Effects of Context. Cognition, 112(1), 21-54.
Griffiths, T., Steyvers, M., & Tenenbaum, J. (2007). Topics in Semantic Representation. Psychological Review, 114(2), 211-244.
Hsu, A. & Griffiths, T. (2009). Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning. Advances in Neural Information Processing Systems 22.
Johnson, K. (2004). Gold's Theorem and Cognitive Science. Philosophy of Science, 71, 571-592.
Kam, X., Stoyneshka, I., Tornyova, L., Fodor, J.D., and Sakas, W. (2008). Bigrams and the Richness of the Stimulus. Cognitive Science, 32(4), 771-787.
Kemp, C., Perfors, A., Tenenbaum, J. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.
Landauer, T.K., & Dumais, S.T. (1997). A solution to Plato's problem: The Latent Semantic Analysis theory of acquisition, induction and representation of knowledge. Psychological Review, 104, 211-240.
McMurray, B. & Hollich, G. (2009). Core computational principals of language acquisition: can statistical learning do the job? Introduction to Special Section. Developmental Science, 12(3), 365-368.
Mintz, T. (2003). Frequent frames as a cue for grammatical categories in child directed speech. Cognition, 90, 91-117.
Navarro, D., Griffiths, T., Steyvers, M., and Lee, M. (2006). Modeling individual differences using Dirichlet processes. Journal of Mathematical Psychology, 50, 101-122.
Pearl, L., Goldwater, S., & Steyvers, M. (2010). How Ideal Are We? Incorporating Human Limitations into Bayesian Models of Word Segmentation. BUCLD 34: Proceedings of the 34th annual Boston University Conference on Child Language Development, Somerville, MA: Cascadilla Press.
Pearl, L. & Lidz, J. (2009). When domain-general learning fails and when it succeeds: Identifying the contribution of domain-specificity. Language Learning & Development, 5(4), 235-265.
Perfors, A., Tenenbaum, J., Gibson, T., and Regier, T. (forthcoming). How recursive is language? A Bayesian exploration. Linguistic Review.
Perfors, A., Tenenbaum, J., & Regier, T. (2006). Poverty of the Stimulus? A Rational Approach. In R. Sun & N. Miyake (eds.) Proceedings of the 28th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society: 663-668.
Perfors, A., Tenenbaum, J., & Regier, T. (under review). The learnability of abstract syntactic principles. Ms.
Reali, F. & Christiansen, M. (2005). Structure Dependence in Language Acquisition: Uncovering the Richness of the Stimulus: Stucture Dependence and Indirect Statistical Evidence, Cognitive Science, 29, 1007-1028.
Regier, T., and Gahl, S. (2004). Learning the unlearnable: the role of missing evidence. Cognition, 93, 147-155.
Samuelson, L. (2009). A core principle of studying language acquisition: it's a developmental system. Developmental Science, 12(3), 407-409.
Shi, L., Griffiths, T. L., Feldman, N. H, & Sanborn, A. N. (in press). Exemplar models as a mechanism for performing Bayesian inference. Psychonomic Bulletin & Review.
Soderstrom, M., Conwell, E., Feldman, N., Morgan, J. (2009). The learner as statistician: three principles of computational success in language acquisition. Developmental Science, 12(3), 409-411.
Steyvers, M. & Griffiths, T. (2007). Probabilistic topic models. In T. Landauer, D. S. McNamara, S. Dennis, & W. Kintsch (Eds.), Handbook of Latent Semantic Analysis. Hillsdale, NJ: Erlbaum.
Udden, J., Araujo, S., Forkstam, C., Ingvar, M., Hagoort, P., & Petersson, K. M. (2009). A matter of time: Implicit acquisition of recursive sequence structures. In N. Taatgen, & H. Van Rijn (Eds.), Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, 2444-2449.
Xu, F., & Tenenbaum, J. (2007). Word Learning as Bayesian Inference, Psychological Review, 114(2), 245-272.