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Thomas G. Dietterich
Researcher at Oregon State University
Publications - 286
Citations - 58937
Thomas G. Dietterich is an academic researcher from Oregon State University. The author has contributed to research in topics: Reinforcement learning & Markov decision process. The author has an hindex of 74, co-authored 279 publications receiving 51935 citations. Previous affiliations of Thomas G. Dietterich include University of Wyoming & Stanford University.
Papers
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Proceedings Article
Open Category Detection with PAC Guarantees
TL;DR: This paper develops an algorithm with PAC-style guarantees on the alien detection rate, while aiming to minimize false alarms, and demonstrates the regimes in which the algorithm can be effective and provide a baseline for further advancements.
Journal ArticleDOI
Learning first-order probabilistic models with combining rules
TL;DR: A language that consists of quantified conditional influence statements and captures most relational probabilistic models based on directed graphs is described and algorithms based on gradient descent and expectation maximization for different combining rules are derived and implemented.
Proceedings Article
Active imitation learning via reduction to I.I.D. active learning
TL;DR: This paper considers active imitation learning with the goal of reducing this effort by querying the expert about the desired action at individual states, which are selected based on answers to past queries and the learner's interactions with an environment simulator.
Proceedings Article
Approximate Inference in Collective Graphical Models
TL;DR: A tractable convex approximation to the NP-hard MAP inference problem in CGMs is developed, and it is demonstrated empirically that these approximation techniques can reduce the computational cost of inference and the cost of learning by at least an order of magnitude while providing solutions of equal or better quality.
Proceedings ArticleDOI
Detecting and correcting user activity switches: algorithms and interfaces
Jianqiang Shen,Jed Irvine,Xinlong Bao,Michael Wayne Goodman,Stephen Kolibaba,Anh Tran,Fredric Carl,Brenton Kirschner,Simone Stumpf,Thomas G. Dietterich +9 more
TL;DR: This paper presents TaskPredictor2, a complete redesign of the activity predictor in TaskTracer and its notification user interface that applies a novel online learning algorithm that is able to incorporate a richer set of features than the authors' previous predictors.