35 found
Sort by:
See also:
Profile: Michael Joseph Lee (Pepperdine University, University of Southern California)
  1. Michael David Lee, B. M. Pincombe & Matthew Brian Welsh (forthcoming). An Empirical Evaluation of Models of Text Document Similarity. Cognitive Science.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  2. Daniel Joseph Navarro, Michael David Lee & H. C. Nikkerud (forthcoming). Learned Categorical Perception for Natural Faces. Cognitive Science.
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  3. Don Ravenzwaaij, Chris P. Moore, Michael D. Lee & Ben R. Newell (2014). A Hierarchical Bayesian Modeling Approach to Searching and Stopping in Multi‐Attribute Judgment. Cognitive Science 38 (2):1384-1405.
    In most decision-making situations, there is a plethora of information potentially available to people. Deciding what information to gather and what to ignore is no small feat. How do decision makers determine in what sequence to collect information and when to stop? In two experiments, we administered a version of the German cities task developed by Gigerenzer and Goldstein (1996), in which participants had to decide which of two cities had the larger population. Decision makers were not provided with the (...)
    Direct download (4 more)  
     
    My bibliography  
     
    Export citation  
  4. Michael D. Lee & Wolf Vanpaemel (2013). Quantum Models of Cognition as Orwellian Newspeak. Behavioral and Brain Sciences 36 (3):295-296.
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  5. Michael G. Lee (2013). The German Mittelweg: Garden Theory and Philosophy in the Time of Kant. Routledge.
    In the 1790s, a close-knit group of German philosophers published several garden theory texts. These works are unique in that a close-knit group of philosophers had never before--and has not since--produced so many works on the topic of garden design. In essence, this cohort sought to imbue the most visionary concepts that had been inherited from the German garden tradition with the intellectual resources that were newly available through Kant’s critical philosophy. The most important of these concepts was the prescription (...)
     
    My bibliography  
     
    Export citation  
  6. Michael D. Lee, Mark Steyvers, Mindy de Young & Brent Miller (2012). Inferring Expertise in Knowledge and Prediction Ranking Tasks. Topics in Cognitive Science 4 (1):151-163.
    We apply a cognitive modeling approach to the problem of measuring expertise on rank ordering problems. In these problems, people must order a set of items in terms of a given criterion (e.g., ordering American holidays through the calendar year). Using a cognitive model of behavior on this problem that allows for individual differences in knowledge, we are able to infer people's expertise directly from the rankings they provide. We show that our model-based measure of expertise outperforms self-report measures, taken (...)
    Direct download (7 more)  
     
    My bibliography  
     
    Export citation  
  7. Toni E. Lin, Chrisovalantis Lakhiani, Michael R. Lee, Michel Saint-Cyr & Douglas M. Sammer (2012). Biomechanical Analysis of Knotless Flexor Tendon Repair Using Large-Diameter Unidirection Barbed Suture. In Zdravko Radman (ed.), The Hand. Mit Press.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  8. Daniel J. Navarro, Matthew J. Dry & Michael D. Lee (2012). Sampling Assumptions in Inductive Generalization. Cognitive Science 36 (2):187-223.
    Inductive generalization, where people go beyond the data provided, is a basic cognitive capability, and it underpins theoretical accounts of learning, categorization, and decision making. To complete the inductive leap needed for generalization, people must make a key ‘‘sampling’’ assumption about how the available data were generated. Previous models have considered two extreme possibilities, known as strong and weak sampling. In strong sampling, data are assumed to have been deliberately generated as positive examples of a concept, whereas in weak sampling, (...)
    Direct download (7 more)  
     
    My bibliography  
     
    Export citation  
  9. Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee & Matthew J. Dry (2012). The Wisdom of the Crowd in Combinatorial Problems. Cognitive Science 36 (3):452-470.
    The “wisdom of the crowd” phenomenon refers to the finding that the aggregate of a set of proposed solutions from a group of individuals performs better than the majority of individual solutions. Most often, wisdom of the crowd effects have been investigated for problems that require single numerical estimates. We investigate whether the effect can also be observed for problems where the answer requires the coordination of multiple pieces of information. We focus on combinatorial problems such as the planar Euclidean (...)
    Direct download (7 more)  
     
    My bibliography  
     
    Export citation  
  10. Michael D. Lee (2011). In Praise of Ecumenical Bayes. Behavioral and Brain Sciences 34 (4):206-207.
    Jones & Love (J&L) should have given more attention to Agnostic uses of Bayesian methods for the statistical analysis of models and data. Reliance on the frequentist analysis of Bayesian models has retarded their development and prevented their full evaluation. The Ecumenical integration of Bayesian statistics to analyze Bayesian models offers a better way to test their inferential and predictive capabilities.
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  11. Michael D. Lee & Barbara W. Sarnecka (2011). Number-Knower Levels in Young Children: Insights From Bayesian Modeling. Cognition 120 (3):391-402.
  12. Veljko Jeremic, Dragan Vukmirovic, Zoran Radojicic, Todd M. Gureckis, Bradley C. Love, Michael D. Lee, Barbara W. Sarnecka, Bruno Estigarribia, Kentaro Nakatani & Edward Gibson (2010). Subject Index to Volume 34. Cognitive Science 34:1596-1601.
    No categories
    Direct download (2 more)  
     
    My bibliography  
     
    Export citation  
  13. Michael D. Lee (2010). Emergent and Structured Cognition in Bayesian Models: Comment on Griffiths Et Al. And McClelland Et Al. Trends in Cognitive Sciences 14 (8):345-346.
  14. Michael D. Lee & Barbara W. Sarnecka (2010). A Model of Knower‐Level Behavior in Number Concept Development. Cognitive Science 34 (1):51-67.
    Direct download (4 more)  
     
    My bibliography  
     
    Export citation  
  15. Michael D. Lee & Jenny Shi (2010). The Accuracy of Small-Group Estimation and the Wisdom of Crowds. In. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. 1124--1129.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  16. Michael D. Lee & Ruud Wetzels (2010). Individual Differences in Attention During Category Learning. In. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. 387--392.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  17. Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee & Matthew Dry (2010). Wisdom of Crowds in Minimum Spanning Tree Problems. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  18. Matthew D. Zeigenfuse & Michael D. Lee (2010). Heuristics for Choosing Features to Represent Stimuli. In. In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. 1565--1570.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  19. Matthew J. Dry, Daniel J. Navarro, Kym Preiss & Michael D. Lee (2009). The Perceptual Organization of Point Constellations. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  20. Ben R. Newell & Michael D. Lee (2009). Learning to Adapt Evidence Thresholds in Decision Making. In. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  21. Matthew B. Welsh, Michael D. Lee & Steve H. Begg (2009). Repeated Judgments in Elicitation Tasks: Efficacy of the MOLE Method. In. In N. A. Taatgen & H. van Rijn (eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  22. Michael D. Lee & Wolf Vanpaemel (2008). Exemplars, Prototypes, Similarities, and Rules in Category Representation: An Example of Hierarchical Bayesian Analysis. Cognitive Science 32 (8):1403-1424.
  23. Daniel J. Navarro, Michael D. Lee, Matthew J. Dry & Benjamin Schultz (2008). Extending and Testing the Bayesian Theory of Generalization. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  24. Richard M. Shiffrin, Michael D. Lee, Woojae Kim & Eric‐Jan Wagenmakers (2008). A Survey of Model Evaluation Approaches With a Tutorial on Hierarchical Bayesian Methods. Cognitive Science 32 (8):1248-1284.
  25. Richard M. Shiffrin, Michael D. Lee, Eric-Jan Wagenmakers & W. J. Kim (2008). Model Evaluation and Selection: Established Methods and Recent Developments. Cognitive Science 32.
     
    My bibliography  
     
    Export citation  
  26. Joachim Vandekerckhove, Francis Tuerlinckx & Michael Lee (2008). A Bayesian Approach to Diffusion Process Models of Decision-Making. In. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. 1429--1434.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  27. Matthew D. Zeigenfuse & Michael D. Lee (2008). Finding Feature Representations of Stimuli: Combining Feature Generation and Similarity Judgment Tasks. In. In B. C. Love, K. McRae & V. M. Sloutsky (eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society. Cognitive Science Society. 1825--1830.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation  
  28. Michael D. Lee (2006). A Hierarchical Bayesian Model of Human Decision‐Making on an Optimal Stopping Problem. Cognitive Science 30 (3):1-26.
  29. Michael D. Lee & Matthew J. Dry (2006). Decision Making and Confidence Given Uncertain Advice. Cognitive Science 30 (6):1081-1095.
    Direct download (4 more)  
     
    My bibliography  
     
    Export citation  
  30. Michael D. Lee & Elissa Y. Corlett (2003). Sequential Sampling Models of Human Text Classification. Cognitive Science 27 (2):159-193.
    Direct download (6 more)  
     
    My bibliography  
     
    Export citation  
  31. Michael Ramscar, Daniel Yarlett, Shimon Edelman, Nathan Intrator, Gergely Csibra, Szilvia Bıró, Orsolya Koós, György Gergely, Holk Cruse & Michael D. Lee (2003). Regular Articles Learning to Divide the Labor: An Account of Deficits in Light and Heavy Verb Production 1 Jean K. Gordon, Gary S. Dell Semantic Grounding in Models of Analogy: An Environmental Approach 41. Cognitive Science 27:945-948.
    Direct download  
     
    My bibliography  
     
    Export citation  
  32. Michael Lee & Mieczyslaw Wolsan (2002). Integration, Individuality and Species Concepts. Biology and Philosophy 17 (5):651-660.
    Integration (interaction among parts of an entity) is suggested to be necessary for individuality (contra, Metaphysics and the Origin of Species). A synchronic species is an integrated individual that can evolve as a unified whole; a diachronic lineage is a non-integrated historical entity that cannot evolve. Synchronic species and diachronic lineages are consequently suggested to be ontologically distinct entities, rather than alternative perspectives of the same underlying entity (contra Baum (1998), Syst. Biol. 47, 641–653; de Queiroz (1995), Endless Forms: Species (...)
    Direct download (5 more)  
     
    My bibliography  
     
    Export citation  
  33. Michael D. Lee (2001). Extending Bayesian Concept Learning to Deal with Representational Complexity and Adaptation. Behavioral and Brain Sciences 24 (4):685-686.
    While Tenenbaum and Griffiths impressively consolidate and extend Shepard's research in the areas of stimulus representation and generalization, there is a need for complexity measures to be developed to control the flexibility of their “hypothesis space” approach to representation. It may also be possible to extend their concept learning model to consider the fundamental issue of representational adaptation. [Tenenbaum & Griffiths].
    Direct download (3 more)  
     
    My bibliography  
     
    Export citation  
  34. Douglas Vickers & Michael D. Lee (1997). Towards a Dynamic Connectionist Model of Memory. Behavioral and Brain Sciences 20 (1):40-41.
    Glenberg's account falls short in several respects. Besides requiring clearer explication of basic concepts, his account fails to recognize the autonomous nature of perception. His account of what is remembered, and its description, is too static. His strictures against connectionist modeling might be overcome by combining the notions of psychological space and principled learning in an embodied and situated network.
    Direct download (5 more)  
     
    My bibliography  
     
    Export citation  
  35. Linda Ganzini, Michael A. Lee, R. T. Heintz & J. D. Bloom (1993). Depression, Suicide, and the Right to Refuse Life-Sustaining Treatment. Journal of Clinical Ethics 4 (4):337.
    No categories
    Direct download  
     
    My bibliography  
     
    Export citation