A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
[PDF][PDF] A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - Transportation Research Part B: Methodological, 2022 - par.nsf.gov
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - Transportation Research Part B …, 2022 - ui.adsabs.harvard.edu
An AMXL model is proposed with individual-level parameter specification. A quadratic
inverse optimization model is proposed to estimate the parameters. A decomposition …
inverse optimization model is proposed to estimate the parameters. A decomposition …
A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - Transportation Research Part B: Methodological, 2022 - trid.trb.org
The authors propose an agent-based mixed-logit model (AMXL) that is estimated with
inverse optimization (IO) estimation, an agent-level machine learning method theoretically …
inverse optimization (IO) estimation, an agent-level machine learning method theoretically …
A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - Transportation Research Part B …, 2022 - nyuscholars.nyu.edu
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
[PDF][PDF] A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - researchgate.net
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - Transportation Research Part B: Methodological, 2022 - ideas.repec.org
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - Transportation Research Part B …, 2022 - econpapers.repec.org
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - Transportation Research Part B: Methodological, 2022 - Elsevier
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …
[PDF][PDF] A random-utility-consistent machine learning method to estimate agents' joint activity scheduling choice from a ubiquitous data set
X Ren, JYJ Chow - researchgate.net
We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …
optimization (IO) estimation, an agent-level machine learning method theoretically …