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Filtering by: Creator Durkina, Valentina B Contributor advisor sim Dietterich, Thomas G.

Learning cost-sensitive diagnostic policies from data

Creator:

Zubek, Valentina Bayer

Abstract:

In its simplest form, the process of diagnosis is a decision-making process in which the diagnostician performs a sequence of tests culminating in a diagnostic decision. For example, a physician might perform a series of simple measurements (body tem- perature, weight, etc.) and laboratory measurements (white blood count, CT scan,...

Resource Type:

Dissertation

Full Text:

corrected_thesis.dvi AN ABSTRACT OF THE DISSERTATION OF Valentina
Methods for cost-sensitive learning

Creator:

Margineantu, Dragos D.

Abstract:

Many approaches for achieving intelligent behavior of automated (computer) systems involve components that learn from past experience. This dissertation studies computational methods for learning from examples, for classification and for decision making, when the decisions have different non-zero costs associated with them. Many practical applications of learning algorithms, including transaction...

Resource Type:

Dissertation

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, bagged lazy option trees (B-LOTs), that gives better probability estimates than any previous method
Model-based approximation methods for reinforcement learning

Creator:

Wang, Xin

Abstract:

The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...

Resource Type:

Dissertation

Full Text:

, encouragement, and help during the first couple of years, and Bill Langford, Valentina Bayer Zubek, and Dragos