Michael T. Lash

25 papers A 1Journal 19Unranked 5
YearRankTypeTitle / Venue / Authors
2024 J jnl
HEX: Human-in-the-loop explainability via deep reinforcement learning.
Decis. Support Syst.
Michael T. Lash
2024 J jnl
Impact of the COVID-19 pandemic on the stock market and investor online word of mouth.
Decis. Support Syst.
Xiaorui Zhu, Shaobo Li, Karthik Srinivasan, Michael T. Lash
2024 J jnl
The third party logistics provider freight management problem: a framework and deep reinforcement learning approach.
Ann. Oper. Res.
Amin Abbasi-Pooya, Michael T. Lash
2022 J jnl
HEX: Human-in-the-loop Explainability via Deep Reinforcement Learning.
CoRR
Michael T. Lash
2021 J jnl
Optimal sepsis patient treatment using human-in-the-loop artificial intelligence.
Expert Syst. Appl.
Akash Gupta, Michael T. Lash, Senthil K. Nachimuthu
2020 J jnl
Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence.
CoRR
Akash Gupta, Michael T. Lash, Senthil K. Nachimuthu
2020 — conf
Personalized Cardiovascular Disease Risk Mitigation via Longitudinal Inverse Classification.
BIBM
Michael T. Lash, W. Nick Street
2020 J jnl
Personalized Cardiovascular Disease Risk Mitigation via Longitudinal Inverse Classification.
CoRR
Michael T. Lash, W. Nick Street
2019 J jnl
21 Million Opportunities: a 19 Facility Investigation of Factors Affecting Hand-Hygiene Compliance via Linear Predictive Models.
J. Heal. Informatics Res.
Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre
2018 J jnl
21 Million Opportunities: A 19 Facility Investigation of Factors Affecting Hand Hygiene Compliance via Linear Predictive Models.
CoRR
Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre
2018 J jnl
Deriving Enhanced Geographical Representations via Similarity-based Spectral Analysis: Predicting Colorectal Cancer Survival Curves in Iowa.
CoRR
Michael T. Lash, Min Zhang, Xun Zhou, W. Nick Street, Charles F. Lynch
2018 J jnl
Deriving enhanced geographical representations via similarity-based spectral analysis: predicting colorectal cancer survival curves in Iowa.
Int. J. Data Min. Bioinform.
Michael T. Lash, Min Zhang, Xun Zhou, W. Nick Street, Charles F. Lynch
2018 J jnl
Prophit: Causal inverse classification for multiple continuously valued treatment policies.
CoRR
Michael T. Lash, Qihang Lin, W. Nick Street
2017 — conf
A Budget-Constrained Inverse Classification Framework for Smooth Classifiers.
ICDM Workshops
Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson
2017 — conf
A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models.
ICHI
Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre
2017 J jnl
A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models.
CoRR
Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre
2017 A conf
Generalized Inverse Classification.
SDM
Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson, Jeffrey W. Ohlmann
2017 J jnl
Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State of Iowa.
CoRR
Michael T. Lash, Yuqi Sun, Xun Zhou, Charles F. Lynch, W. Nick Street
2017 — conf
Learning rich geographical representations: Predicting colorectal cancer survival in the state of Iowa.
BIBM
Michael T. Lash, Yuqi Sun, Xun Zhou, Charles F. Lynch, W. Nick Street
2016 J jnl
A budget-constrained inverse classification framework for smooth classifiers.
CoRR
Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson
2016 J jnl
Early Predictions of Movie Success: The Who, What, and When of Profitability.
J. Manag. Inf. Syst.
Michael T. Lash, Kang Zhao
2016 J jnl
Generalized Inverse Classification.
CoRR
Michael T. Lash, Qihang Lin, W. Nick Street, Jennifer G. Robinson, Jeffrey W. Ohlmann
2016 J jnl
Realistic risk-mitigating recommendations via inverse classification.
CoRR
Michael T. Lash, W. Nick Street
2015 — conf
Early Prediction of Movie Success - What, Who, and When.
SBP
Michael T. Lash, Sunyang Fu, Shiyao Wang, Kang Zhao
2015 J jnl
Early Predictions of Movie Success: the Who, What, and When of Profitability.
CoRR
Michael T. Lash, Kang Zhao