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I am an Assistant Professor at CMU's Department of Psychology.
Email: Phone: (412) 268 4680 (office)
Mail: Department of Psychology
Research InterestsI work on computational models of learning and development. Humans regularly make inferences that go beyond the data they have observed, and I attempt to characterize the knowledge that supports these inferences and to explain how this knowledge might be acquired. I am particularly interested in high-level cognition, and have developed models of categorization, property induction, word-learning, causal reasoning, similarity, and relational learning. |
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Representative PapersKemp, C., Tenenbaum, J. B., Niyogi, S. & Griffiths, T. L. (in press) A probabilistic model of theory formation. Cognition. Code and data sets. Kemp, C. & Jern, A. (2009). A taxonomy of inductive problems. Proceedings of the 31st Annual Conference of the Cognitive Science Society. Kemp, C., & Tenenbaum, J. B. (2009). Structured statistical models of inductive reasoning. Psychological Review. 116(1), 20-58. Data sets. Kemp, C., & Tenenbaum, J. B. (2008). The discovery of structural form. Proceedings of the National Academy of Sciences. 105(31), 10687-10692.   Supporting information.  Commentary by K. J. Holyoak.  Code and data sets. Kemp, C., Perfors, A. & Tenenbaum, J. B. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321. |
Other PapersIn pressKemp, C., Chang, K. K. & Lombardi, L. (in press). Category and feature identification. Acta Psychologica. Kemp, C. & Jern, A. (in press). Abstraction and relational learning. Advances in Neural Information Processing Systems 22. Kemp, C. (in press). Quantification and the language of thought. Advances in Neural Information Processing Systems 22. Jern, A., Chang, K. K. & Kemp, C. (in press). Bayesian belief polarization. Advances in Neural Information Processing Systems 22. Supporting material Kemp, C., Jern, A. & Xu, F. (in press). Object discovery and identification. Advances in Neural Information Processing Systems 22. 2009Jern, A. & Kemp, C. (2009). Category generation. Proceedings of the 31st Annual Conference of the Cognitive Science Society. Maas, A. L. & Kemp, C. (2009). One-shot learning with Bayesian networks. Proceedings of the 31st Annual Conference of the Cognitive Science Society. Kemp, C. & Xu, F. (2009). An ideal observer model of infant object perception. Advances in Neural Information Processing Systems 21. Supporting material 2008Kemp, C. & Tenenbaum, J. B. (2008). Structured models of semantic cognition. Behavioral and Brain Sciences. 31(6), 717-718. Kemp, C., Goodman, N. D. & Tenenbaum, J. B. (2008). Learning and using relational theories. Advances in Neural Information Processing Systems 20. Supporting material Griffiths, T. L., Kemp, C., & Tenenbaum, J. B. (2008). Bayesian models of cognition. In Ron Sun (ed.), The Cambridge handbook of computational cognitive modeling. Cambridge University Press. Kemp, C., Goodman, N. D. & Tenenbaum, J. B. (2008). Theory acquisition and the language of thought. Proceedings of the 30th Annual Conference of the Cognitive Science Society. 2007Kemp, C. (2007). The acquisition of inductive constraints. Ph.D. thesis, MIT. Kemp, C., Goodman, N. D. & Tenenbaum, J. B. (2007). Learning causal schemata. Proceedings of the 29th Annual Conference of the Cognitive Science Society. Prize for computational modeling of high level cognition Kemp, C., Shafto, P., Berke, A. & Tenenbaum, J. B. (2007). Combining causal and similarity-based reasoning. Advances in Neural Information Processing Systems 19. Honorable mention, Outstanding Student Paper award Roy, D. M., Kemp, C., Mansinghka, V., & Tenenbaum, J. B. (2007). Learning annotated hierarchies from relational data. Advances in Neural Information Processing Systems 19. 2006Kemp, C., Tenenbaum, J. B., Griffiths, T. L., Yamada, T. & Ueda, N. (2006). Learning systems of concepts with an infinite relational model. Proceedings of the 21st National Conference on Artificial Intelligence. Code and data sets. Tenenbaum, J. B., Griffiths, T. L. & Kemp, C. (2006). Theory-based Bayesian models of inductive learning and reasoning. Trends in Cognitive Sciences, 10(7), 309-318. Kemp, C., Perfors, A. & Tenenbaum, J. B. (2006). Learning overhypotheses. Proceedings of the 28th Annual Conference of the Cognitive Science Society. Schmidt, L. A., Kemp, C. & Tenenbaum, J. B. (2006). Nonsense and sensibility: inferring unseen possibilities. Proceedings of the 28th Annual Conference of the Cognitive Science Society. Shafto, P., Kemp, C., Mansinghka, V., Gordon, M. & Tenenbaum, J. B. (2006). Learning cross-cutting systems of categories. Proceedings of the 28th Annual Conference of the Cognitive Science Society. Mansinghka, V. K., Kemp, C., Tenenbaum, J. B. & Griffiths, T. L. (2006). Structured priors for structure learning. Proceedings of the 22nd Conference on Uncertainty in Artificial Intelligence. 2005Kemp, C., Bernstein, A. & Tenenbaum, J. B. (2005). A generative theory of similarity. Proceedings of the 27th Annual Conference of the Cognitive Science Society. Stimuli and derivations. Shafto, P., Kemp, C., Baraff, E., Coley, J. D. & Tenenbaum, J. B. (2005). Context-sensitive induction. Proceedings of the 27th Annual Conference of the Cognitive Science Society. Kemp, C., Griffiths, T. L. & Tenenbaum, J. B. (2004). Discovering latent classes in relational data. AI Memo 2004-019 2004Kemp, C., Perfors, A. & Tenenbaum, J. B. (2004). Learning domain structures. Proceedings of the 26th Annual Conference of the Cognitive Science Society. Kemp, C., Griffiths, T. L., Stromsten, S., & Tenenbaum, J. B. (2004). Semi-supervised learning with trees. Advances in Neural Information Processing Systems 16. The proof of the theorem stated in the paper. 2003Kemp, C. & Tenenbaum, J. B. (2003). Theory-based induction. Proceedings of the 25th Annual Conference of the Cognitive Science Society. 2002Kemp, C. & Ramamohanarao, K. (2002). Long term learning for web search engines. Proceedings of the 6th European Conference on Principles and Practice of Knowledge Discovery in Databases. |