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ORCIDMichael D. Lee 0001
Person information
- affiliation: University of California, Irvine, Department of Cognitive Sciences, CA, USA
- affiliation (former): Defence Science Technology Organisation, Salisbury, SA, Australia
- affiliation (former): University of Adelaide, Department of Psychology, Australia
Other persons with the same name
- Michael D. Lee 0002
![[0000-0001-7750-9145]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7750-9145")
— NASA Ames Research Center, Exobiology Branch, Moffett Field, CA, USA - Michael D. Lee 0003 — The MITRE Corporation, Dumfries, VA, USA
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2020 – today
- 2022
[c27]Lauren E. Montgomery, Michael D. Lee:
The Wisdom of the Crowd and Framing Effects in Spatial Knowledge. CogSci 2022- [c26]Manuel Villarreal, Sahar Vaday, Michael D. Lee:
Categorization in Environments that Change when People Learn. CogSci 2022 - [c25]Holly A. Westfall, Michael D. Lee:
A model of free recall for multiple encounters of semantically related stimuli with an application to understanding cognitive impairment. CogSci 2022 - 2021
- [j25]Bobby Thomas, Jeff Coon, Holly A. Westfall, Michael D. Lee:
Model-Based Wisdom of the Crowd for Sequential Decision-Making Tasks. Cogn. Sci. 45(7) (2021) - [c24]Michael G. Collins, Alexander Hough, Michael D. Lee, Jayde King:
Exploring Online Goal Inference in Real World Environments. CogSci 2021 - [c23]Holly A. Westfall, Michael D. Lee:
A Model-Based Analysis of Changes in the Semantic Structure of Free Recall Due to Cognitive Impairment. CogSci 2021 - 2020
- [c22]Alexander Hough, Kevin A. Gluck, Michael D. Lee:
Strategy Inference and Switch Detection Method Generalizes to Category Learning. CogSci 2020
2010 – 2019
- 2018
- [c21]Percy Mistry, Joshua C. Skewes, Michael D. Lee:
An Adaptive Signal Detection Model applied to Perceptual Learning. CogSci 2018 - 2016
- [c20]Irina Danileiko, Michael D. Lee:
Inferring Individual Differences Between and Within Exemplar and Decision-Bound Models of Categorization. CogSci 2016 - [c19]Percy Mistry, Michael D. Lee, Ben R. Newell:
An Empirical Evaluation of Models for How People Learn Cue Search Orders. CogSci 2016 - 2015
- [c18]Irina Danileiko, Michael D. Lee, Michael L. Kalish:
A Bayesian Latent Mixture Approach to Modeling Individual Differences in Categorization Using General Recognition Theory. CogSci 2015 - [c17]Maime Guan, Michael D. Lee, Joachim Vandekerckhove:
A Hierarchical Cognitive Threshold Model of Human Decision Making on Different Length Optimal Stopping Problems. CogSci 2015 - [c16]Michael D. Lee, Emily Liu, Mark Steyvers:
The Roles of Knowledge and Memory in Generating Top-10 Lists. CogSci 2015 - 2014
- [j24]Don van Ravenzwaaij, Chris P. Moore, Michael D. Lee, Ben R. Newell:
A Hierarchical Bayesian Modeling Approach to Searching and Stopping in Multi-Attribute Judgment. Cogn. Sci. 38(7): 1384-1405 (2014) - [c15]Maime Guan, Michael D. Lee, Andy Silva:
Threshold Models of Human Decision Making on Optimal Stopping Problems in Different Environments. CogSci 2014 - [c14]Sean Tauber, Daniel J. Navarro, Amy Perfors, Michael D. Lee:
Inferring the hypothesis spaces underlying inductive generalization. CogSci 2014 - 2013
- [c13]Don van Ravenzwaaij, Ben R. Newell, Chris P. Moore, Michael D. Lee:
Using Recognition in Multi-Attribute Decision Environments. CogSci 2013 - 2012
- [j23]Daniel J. Navarro, Matthew J. Dry, Michael D. Lee:
Sampling Assumptions in Inductive Generalization. Cogn. Sci. 36(2): 187-223 (2012) - [j22]Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee, Matthew J. Dry:
The Wisdom of the Crowd in Combinatorial Problems. Cogn. Sci. 36(3): 452-470 (2012) - [j21]Marcus A. Butavicius, Michael D. Lee, Brandon M. Pincombe, Louise G. Mullen, Daniel J. Navarro, Kathryn Parsons, Agata McCormac:
An assessment of email and spontaneous dialog visualizations. Int. J. Hum. Comput. Stud. 70(6): 432-449 (2012) - [j20]Michael D. Lee, Mark Steyvers, Mindy de Young, Brent Miller:
Inferring Expertise in Knowledge and Prediction Ranking Tasks. Top. Cogn. Sci. 4(1): 151-163 (2012) - [c12]Derrik E. Asher, Shunan Zhang, Andrew Zaldivar, Michael D. Lee, Jeffrey L. Krichmar:
Modeling individual differences in socioeconomic game playing. CogSci 2012 - 2011
- [j19]Michael D. Lee, Shunan Zhang, Miles Munro, Mark Steyvers:
Psychological models of human and optimal performance in bandit problems. Cogn. Syst. Res. 12(2): 164-174 (2011) - [c11]Michael D. Lee, Mark Steyvers, Mindy de Young, Brent Miller:
A Model-Based Approach to Measuring Expertise in Ranking Tasks. CogSci 2011 - [c10]James Pooley, Michael D. Lee, William Shankle:
Modeling Multitrial Free Recall with Unknown Rehearsal Times. CogSci 2011 - [c9]Matthew D. Zeigenfuse, Michael D. Lee:
A Comparison of Three Measures of the Association Between a Feature and a Concept. CogSci 2011 - [c8]Shunan Zhang, Michael D. Lee, Meng Yu, Jack Xin:
Modeling Category Identification Using Sparse Instance Representation. CogSci 2011 - 2010
- [j18]Michael D. Lee, Barbara W. Sarnecka:
A Model of Knower-Level Behavior in Number Concept Development. Cogn. Sci. 34(1): 51-67 (2010)
2000 – 2009
- 2009
- [j17]Sheng Kung Michael Yi, Mark Steyvers, Michael D. Lee:
Modeling Human Performance in Restless Bandits with Particle Filters. J. Probl. Solving 2(2) (2009) - [c7]Mark Steyvers, Michael D. Lee, Brent Miller, Pernille Hemmer:
The Wisdom of Crowds in the Recollection of Order Information. NIPS 2009: 1785-1793 - 2008
- [j16]Richard M. Shiffrin, Michael D. Lee, Woojae Kim, Eric-Jan Wagenmakers:
A Survey of Model Evaluation Approaches With a Tutorial on Hierarchical Bayesian Methods. Cogn. Sci. 32(8): 1248-1284 (2008) - [j15]Michael D. Lee, Wolf Vanpaemel:
Exemplars, Prototypes, Similarities, and Rules in Category Representation: An Example of Hierarchical Bayesian Analysis. Cogn. Sci. 32(8): 1403-1424 (2008) - [j14]Edward P. Chronicle, James N. MacGregor, Michael D. Lee, Thomas C. Ormerod, Peter Hughes:
Individual Differences in Optimization Problem Solving: Reconciling Conflicting Results. J. Probl. Solving 2(1) (2008) - 2007
- [j13]Marcus A. Butavicius, Michael D. Lee:
An empirical evaluation of four data visualization techniques for displaying short news text similarities. Int. J. Hum. Comput. Stud. 65(11): 931-944 (2007) - [j12]Michael D. Lee, Michael J. Paradowski:
Group Decision-Making on an Optimal Stopping Problem. J. Probl. Solving 1(2) (2007) - 2006
- [j11]Michael D. Lee:
A Hierarchical Bayesian Model of Human Decision-Making on an Optimal Stopping Problem. Cogn. Sci. 30(3): 555-580 (2006) - [j10]Michael D. Lee, Matthew J. Dry:
Decision Making and Confidence Given Uncertain Advice. Cogn. Sci. 30(6): 1081-1095 (2006) - [j9]Nicholas R. Burns, Michael D. Lee, Douglas Vickers:
Are Individual Differences in Performance on Perceptual and Cognitive Optimization Problems Determined by General Intelligence? J. Probl. Solving 1(1) (2006) - [j8]Matthew J. Dry, Michael D. Lee, Douglas Vickers, Peter Hughes:
Human Performance on Visually Presented Traveling Salesperson Problems with Varying Numbers of Nodes. J. Probl. Solving 1(1) (2006) - [c6]Michael D. Lee, Ian G. Fuss, Daniel J. Navarro:
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time. NIPS 2006: 809-816 - 2005
- [c5]Daniel J. Navarro, Michael D. Lee:
An application of minimum description length clustering to partitioning learning curves. ISIT 2005: 587-591 - 2003
- [j7]Michael D. Lee, Elissa Y. Corlett:
Sequential sampling models of human text classification. Cogn. Sci. 27(2): 159-193 (2003) - [j6]Michael D. Lee, Marcus A. Butavicius, Rachel E. Reilly:
Visualizations of binary data: A comparative evaluation. Int. J. Hum. Comput. Stud. 59(5): 569-602 (2003) - [c4]Michael D. Lee, Rachel E. Reilly:
An Empirical Evaluation of Chernoff Faces, Star Glyphs, and Spatial Visualisations for Binary Data. InVis.au 2003: 1-10 - 2002
- [j5]Michael D. Lee:
Generating Additive Clustering Models with Minimal Stochastic Complexity. J. Classif. 19(1): 69-85 (2002) - [j4]Michael D. Lee:
R. Decker and W. Gaul, Eds., Classification and Information Processing at the Turn of the Millennium, Berlin: Springer-Verlag, 2000, 492 pp. J. Classif. 19(1): 183-186 (2002) - [j3]Michael D. Lee:
A Simple Method for Generating Additive Clustering Models with Limited Complexity. Mach. Learn. 49(1): 39-58 (2002) - [c3]Daniel J. Navarro, Michael D. Lee:
Combining Dimensions and Features in Similarity-Based Representations. NIPS 2002: 59-66 - 2001
- [c2]Michael D. Lee:
Fast Text Classification Using Sequential Sampling Processes. Australian Joint Conference on Artificial Intelligence 2001: 309-320 - 2000
- [c1]Douglas Vickers, Daniel J. Navarro, Michael D. Lee:
Towards a transformational approach to perceptual organization. KES 2000: 325-328
1990 – 1999
- 1998
- [j2]Michael D. Lee:
Neural Feature Abstraction from Judgements of Similarity. Neural Comput. 10(7): 1815-1830 (1998) - 1997
- [j1]Michael D. Lee:
The Connectionist Construction of Psychological Spaces. Connect. Sci. 9(4): 323-352 (1997)
Coauthor Index
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