Mark A. Pitt

Publication Activity (10 Years)

Years Active: 1996-2020
Publications (10 Years): 9

Top Topics

Experimental Designs

Computational Model

Top Venues

Top. Cogn. Sci.

Publications

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)
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)
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)
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)
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)
Jorge Chang, Jiseob Kim, Byoung-Tak Zhang, Mark A. Pitt, Jay I. Myung
Modeling Delay Discounting using Gaussian Process with Active Learning. CogSci (2019)
Marjorie Freggens, Mark A. Pitt
The effect of expertise on auditory categorization: a domain-specific or domain-general mechanism? CogSci (2018)
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)
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) (2017)
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)
Jay I. Myung, Mark A. Pitt, Maarten Speekenbrink
Workshop on Optimizing Experimental Designs: Theory, Practice, and Applications. CogSci (2015)
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) (2014)
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)
Hairong Gu, Jay I. Myung, Mark A. Pitt, Zhong-Lin Lu
Adaptive Estimation of Psychometric Slope and Threshold with Differential Evolution. CogSci (2013)
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) (2013)
Mark A. Pitt, Yun Tang
What Should Be the Data Sharing Policy of Cognitive Science? Top. Cogn. Sci. 5 (1) (2013)
Jay I. Myung, Mark A. Pitt
Tutorial on Model Comparison Methods. CogSci (2011)
Mark A. Pitt, Laura Dilley, Michael Tat
Exploring the role of exposure frequency in recognizing pronunciation variants. J. Phonetics 39 (3) (2011)
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)
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) (2010)
Daniel R. Cavagnaro, Mark A. Pitt, Jay I. Myung
Adaptive Design Optimization in Experiments with People. NIPS (2009)
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) (2008)
Eric Fosler-Lussier, Laura Dilley, Na'im R. Tyson, Mark A. Pitt
The buckeye corpus of speech: updates and enhancements. INTERSPEECH (2007)
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) (2005)
Jay I. Myung, Mark A. Pitt, Daniel J. Navarro
Model selection in cognitive science as an inverse problem. Computational Imaging (2005)
Woojae Kim, Daniel J. Navarro, Mark A. Pitt, In Jae Myung
An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science. NIPS (2003)
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)
In Jae Myung, Mark A. Pitt, Shaobo Zhang, Vijay Balasubramanian
The Use of MDL to Select among Computational Models of Cognition. NIPS (2000)
In Jae Myung, Vijay Balasubramanian, Mark A. Pitt
Counting probability distributions: Differential geometry and model selection. Proc. Natl. Acad. Sci. USA 97 (21) (2000)
James M. McQueen, Mark A. Pitt
Transitional probability and phoneme monitoring. ICSLP (1996)