1. video lecture : http://videolectures.net/mlcs07_frank_bmc
2. A probabilistic model of cross-situational word learning from noisy and ambiguous data
3. When the Shoe Fits: Cross-Situational Learning in Realistic Learning Environments
4. Papers
[1] M. C. Frank, N. D. Goodman, J. B. Tenenbaum, A Bayesian framework for cross-situational
      word-learning, Advances in Neural Information Processing Systems, 2007
[2] Regier, Emergent constraints on word-learning : a computational perspective, Trends in Cognitive
, 2003
[3] D. K. Roy, A. P. Pentland, Learning words from sights and sounds : a computational model,
      Cognitive science, 2002
[4] J. M. Siskind, A computational study of cross-situational techniques for learning word-to-meaning
      mappings, Cognition, 1996
[5] L. Smith, C. Yu, Infants rapidly learn word-referent mappings via cross-situational statistics,
      Cognition, 2008
[6] C. Yu, The emergence of links between lexical acquisition and object categorization : a
      computational study, Connection science, 2005
[7] C. Yu, Learning syntax-semantics mappings to bootstrap word learning, Proc. of CogSci'06, 2006 [8] C. Yu, D. H. Ballard, A unified model of early word learning - Integrating statistical and social cues,
      Neurocomputing, 2007
[9] C. Yu, L. B. Smith, Rapid word learning under uncertainty via cross-situational statistics,
      Psychological Science, 2007