activity
20102026
most cited- and -Learning Methods for Estimating Optimal Dynamic Treatment Regimes

183 citations · 348 across the 27 of their papers we have counts for

collaborators
Showing 2018Show all

6 papers · 1 filter

stat.CO2018★ 4 cited

Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Data

Zekun Xu, Eric B. Laber, Ana-Maria Staicu

Wearable devices including accelerometers are increasingly being used to collect high-frequency human activity data in situ. There is tremendous potential to use such data to infor…

stat.ME2018

Generalization error for decision problems

Eric B. Laber, Min Qian

In this entry we review the generalization error for classification and single-stage decision problems. We distinguish three alternative definitions of the generalization error whi…

cs.LG2018★ 1 cited

Thompson Sampling for Pursuit-Evasion Problems

Zhen Li, Nicholas J. Meyer, Eric B. Laber +1

Pursuit-evasion is a multi-agent sequential decision problem wherein a group of agents known as pursuers coordinate their traversal of a spatial domain to locate an agent trying to…

stat.AP2018★ 1 cited

Bayesian Nonparametric Policy Search with Application to Periodontal Recall Intervals

Qian Guan, Brian J. Reich, Eric B. Laber +1

Tooth loss from periodontal disease is a major public health burden in the United States. Standard clinical practice is to recommend a dental visit every six months; however, this…

stat.ML2018

Receiver Operating Characteristic Curves and Confidence Bands for Support Vector Machines

Daniel J. Luckett, Eric B. Laber, Samer S. El-Kamary +5

Many problems that appear in biomedical decision making, such as diagnosing disease and predicting response to treatment, can be expressed as binary classification problems. The co…

stat.ME2018★ 2 cited

Variable selection using pseudo-variables

Wenhao Hu, Eric Laber, Leonard Stefanski

Penalized regression has become a standard tool for model building across a wide range of application domains. Common practice is to tune the amount of penalization to tradeoff bia…