Charles Kemp

I am an Assistant Professor at CMU's Department of Psychology.

Research Interests

I 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.

Papers

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.

Kemp, C., Goodman, N. D. & Tenenbaum, J. B. (2008). Learning and using relational theories. Advances in Neural Information Processing Systems 20. Supporting material

Kemp, 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., Perfors, A. & Tenenbaum, J. B. (2007). Learning overhypotheses with hierarchical Bayesian models. Developmental Science, 10(3), 307-321.

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.

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., 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. IRM code.

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.

Kemp, 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

Kemp, 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.

Kemp, C. & Tenenbaum, J. B. (2003). Theory-based induction. Proceedings of the 25th Annual Conference of the Cognitive Science Society.

Kemp, 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.