Jay I. Myung

18 papers B 10Journal 5Unranked 2
YearRankTypeTitle / Venue / Authors
2020 B conf
Machine Learning Optimizes Assessment: New Insights for the Development of Numerosity Estimation.
CogSci
Sang Ho Lee, Dan Kim, John Opfer, Mark A. Pitt, Jay I. Myung
2020 B conf
The Scaled Target Learning Model: A Novel Computational Model of the Balloon Analogue Risk Task.
CogSci
Ran Zhou, Jay I. Myung, Mark A. Pitt
2019 B conf
Active Learning for a Number-Line Task with Two Design Variables.
CogSci
Sang Ho Lee, Dan Kim, John Opfer, Mark A. Pitt, Jay I. Myung
2019 B conf
Modeling Delay Discounting using Gaussian Process with Active Learning.
CogSci
Jorge Chang, Jiseob Kim, Byoung-Tak Zhang, Mark A. Pitt, Jay I. Myung
2019 B conf
Optimizing the Design of an Experiment using the ADOpy Package: An Introduction and Tutorial.
CogSci
Jay I. Myung, Mark A. Pitt, Jaeyeong Yang, Woo-Young Ahn
2018 B conf
Assessing the Validity of Three Tasks of Risk-Taking Propensity: Behavioral Measure and Computational Modeling.
CogSci
Ran Zhou, Jay I. Myung, Carol Mathews, Mark A. Pitt
2017 J jnl
Planning Beyond the Next Trial in Adaptive Experiments: A Dynamic Programming Approach.
Cogn. Sci.
Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Jay I. Myung
2015 B conf
Workshop on Optimizing Experimental Designs: Theory, Practice, and Applications.
CogSci
Jay I. Myung, Mark A. Pitt, Maarten Speekenbrink
2014 J jnl
A Hierarchical Adaptive Approach to Optimal Experimental Design.
Neural Comput.
Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Mark Steyvers, Jay I. Myung
2014 B conf
A Hierarchical Adaptive Approach to the Optimal Design of Experiments.
CogSci
Woojae Kim, Mark A. Pitt, Zhong-Lin Lu, Mark Steyvers, Hairong Gu, Jay I. Myung
2013 B conf
Adaptive Estimation of Psychometric Slope and Threshold with Differential Evolution.
CogSci
Hairong Gu, Jay I. Myung, Mark A. Pitt, Zhong-Lin Lu
2013 J jnl
Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach.
Manag. Sci.
Daniel R. Cavagnaro, Richard Gonzalez, Jay I. Myung, Mark A. Pitt
2011 B conf
Tutorial on Model Comparison Methods.
CogSci
Jay I. Myung, Mark A. Pitt
2010 J jnl
Adaptive Design Optimization: A Mutual Information-Based Approach to Model Discrimination in Cognitive Science.
Neural Comput.
Daniel R. Cavagnaro, Jay I. Myung, Mark A. Pitt, Janne V. Kujala
2009 — conf
Adaptive Design Optimization in Experiments with People.
NIPS
Daniel R. Cavagnaro, Mark A. Pitt, Jay I. Myung
2008 J jnl
Measuring Model Flexibility With Parameter Space Partitioning: An Introduction and Application Example.
Cogn. Sci.
Mark A. Pitt, Jay I. Myung, Maximiliano Montenegro, James Pooley
2005 — conf
Model selection in cognitive science as an inverse problem.
Computational Imaging
Jay I. Myung, Mark A. Pitt, Daniel J. Navarro
2004 — ch.
Model Comparison Methods.
Numerical Computer Methods, Part D
Jay I. Myung, Mark A. Pitt