21 citations · 35 across the 9 of their papers we have counts for
4 papers · 1 filter
Decision-Directed Data Decomposition
Brent D. Davis, Ethan Jackson, Daniel J. Lizotte
We present an algorithm, Decision-Directed Data Decomposition (D4), which decomposes a dataset into two components. The first contains most of the useful information for a specifie…
Generative Multiple-Instance Learning Models For Quantitative Electromyography
Tameem Adel, Benn Smith, Ruth Urner +2
We present a comprehensive study of the use of generative modeling approaches for Multiple-Instance Learning (MIL) problems. In MIL a learner receives training instances grouped to…
Budgeted Learning of Naive-Bayes Classifiers
Daniel J. Lizotte, Omid Madani, Russell Greiner
Frequently, acquiring training data has an associated cost. We consider the situation where the learner may purchase data during training, subject TO a budget. IN particular, we ex…
Active Model Selection
Omid Madani, Daniel J. Lizotte, Russell Greiner
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins…