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2020 – today
- 2020
[c21]Sang Ho Lee, Dan Kim, John Opfer, Mark A. Pitt, Jay I. Myung:
Machine Learning Optimizes Assessment: New Insights for the Development of Numerosity Estimation. CogSci 2020- [c20]Ian Miller, Nicolas Dumay, Mark A. Pitt, Brian Lam, Blair C. Armstrong:
Context variability promotes generalization in reading aloud: Insight from a neural network simulation. CogSci 2020 - [c19]Ran Zhou, Jay I. Myung, Mark A. Pitt:
The Scaled Target Learning Model: A Novel Computational Model of the Balloon Analogue Risk Task. CogSci 2020
2010 – 2019
- 2019
- [c18]Jay I. Myung, Mark A. Pitt, Jaeyeong Yang, Woo-Young Ahn:
Optimizing the Design of an Experiment using the ADOpy Package: An Introduction and Tutorial. CogSci 2019: 19-20 - [c17]Sang Ho Lee, Dan Kim, John Opfer, Mark A. Pitt, Jay I. Myung:
Active Learning for a Number-Line Task with Two Design Variables. CogSci 2019: 638 - [c16]Jorge Chang, Jiseob Kim, Byoung-Tak Zhang, Mark A. Pitt, Jay I. Myung:
Modeling Delay Discounting using Gaussian Process with Active Learning. CogSci 2019: 1479-1485 - 2018
- [c15]Marjorie Freggens, Mark A. Pitt:
The effect of expertise on auditory categorization: a domain-specific or domain-general mechanism? CogSci 2018 - [c14]Ran Zhou, Jay I. Myung, Carol Mathews, Mark A. Pitt:
Assessing the Validity of Three Tasks of Risk-Taking Propensity: Behavioral Measure and Computational Modeling. CogSci 2018 - 2017
- [j9]Woojae Kim, Mark A. Pitt, Zhong-Lin Lu
, Jay I. Myung:
Planning Beyond the Next Trial in Adaptive Experiments: A Dynamic Programming Approach. Cogn. Sci. 41(8): 2234-2252 (2017) - 2015
- [c13]Jay I. Myung, Mark A. Pitt, Maarten Speekenbrink:
Workshop on Optimizing Experimental Designs: Theory, Practice, and Applications. CogSci 2015 - [c12]Laura Dilley, Mark A. Pitt, Christine Szostak, Melissa Michaud Baese-Berk:
Rate-dependent speech processing can be speech-specific: Evidence from the disappearance of words under changes in context speech rate. ICPhS 2015 - 2014
- [j8]Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Mark Steyvers, Jay I. Myung:
A Hierarchical Adaptive Approach to Optimal Experimental Design. Neural Comput. 26(11): 2465-2492 (2014) - [c11]Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Mark Steyvers, Hairong Gu, Jay I. Myung:
A Hierarchical Adaptive Approach to the Optimal Design of Experiments. CogSci 2014 - 2013
- [j7]Daniel R. Cavagnaro, Richard Gonzalez, Jay I. Myung, Mark A. Pitt:
Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach. Manag. Sci. 59(2): 358-375 (2013) - [j6]Mark A. Pitt, Yun Tang:
What Should Be the Data Sharing Policy of Cognitive Science? Top. Cogn. Sci. 5(1): 214-221 (2013) - [c10]Hairong Gu, Jay I. Myung, Mark A. Pitt, Zhong-Lin Lu:
Adaptive Estimation of Psychometric Slope and Threshold with Differential Evolution. CogSci 2013 - 2011
- [j5]Mark A. Pitt, Laura Dilley, Michael Tat:
Exploring the role of exposure frequency in recognizing pronunciation variants. J. Phonetics 39(3): 304-311 (2011) - [c9]Jay I. Myung, Mark A. Pitt:
Tutorial on Model Comparison Methods. CogSci 2011 - [c8]Colin Widmer, Dahee Kim, Christine Szostak, Mark A. Pitt:
The use of lexical and duration information in segmenting speech with unclear word boundaries. CogSci 2011 - 2010
- [j4]Daniel R. Cavagnaro, Jay I. Myung, Mark A. Pitt, Janne V. Kujala:
Adaptive Design Optimization: A Mutual Information-Based Approach to Model Discrimination in Cognitive Science. Neural Comput. 22(4): 887-905 (2010)
2000 – 2009
- 2009
- [c7]Daniel R. Cavagnaro, Mark A. Pitt, Jay I. Myung:
Adaptive Design Optimization in Experiments with People. NIPS 2009: 234-242 - 2008
- [j3]Mark A. Pitt, Jay I. Myung, Maximiliano Montenegro, James Pooley:
Measuring Model Flexibility With Parameter Space Partitioning: An Introduction and Application Example. Cogn. Sci. 32(8): 1285-1303 (2008) - 2007
- [c6]Eric Fosler-Lussier, Laura Dilley, Na'im R. Tyson, Mark A. Pitt:
The buckeye corpus of speech: updates and enhancements. INTERSPEECH 2007: 934-937 - 2005
- [j2]Mark A. Pitt, Keith Johnson, Elizabeth Hume, Scott F. Kiesling, William D. Raymond:
The Buckeye corpus of conversational speech: labeling conventions and a test of transcriber reliability. Speech Commun. 45(1): 89-95 (2005) - [c5]Jay I. Myung, Mark A. Pitt, Daniel J. Navarro:
Model selection in cognitive science as an inverse problem. Computational Imaging 2005: 219-228 - 2004
- [p1]Jay I. Myung, Mark A. Pitt:
Model Comparison Methods. Numerical Computer Methods, Part D 2004: 351-366 - 2003
- [c4]Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Jae Myung:
An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science. NIPS 2003: 937-944 - 2002
- [c3]William D. Raymond, Mark A. Pitt, Keith Johnson, Elizabeth Hume, Matthew J. Makashay, Robin Dautricourt, Craig Hilts:
An analysis of transcription consistency in spontaneous speech from the buckeye corpus. INTERSPEECH 2002: 1125-1128 - 2000
- [j1]In Jae Myung, Vijay Balasubramanian, Mark A. Pitt:
Counting probability distributions: Differential geometry and model selection. Proc. Natl. Acad. Sci. USA 97(21): 11170-11175 (2000) - [c2]In Jae Myung, Mark A. Pitt, Shaobo Zhang, Vijay Balasubramanian:
The Use of MDL to Select among Computational Models of Cognition. NIPS 2000: 38-44
1990 – 1999
- 1996
- [c1]James M. McQueen, Mark A. Pitt:
Transitional probability and phoneme monitoring. ICSLP 1996: 2502-2505
Coauthor Index
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