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Filtering by: Creator Kearns, Richard Seng Remove constraint Creator: Kearns, Richard Seng Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Rights Statement In Copyright Remove constraint Rights Statement: In Copyright

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Planning in multi-agent partially observable domains using sparse sampling

Creator:

Donneau-Golencer, Thierry D.

Abstract:

A large number of sequential decision-making problems in uncertain environments can be modeled as Markov Decision Processes (MDPs). In such settings, an agent can observe at each time step the state of the environment and then executes an action, causing a stochastic transition to a new state of the environment...

Resource Type:

Masters Thesis
Toward Automated Decision-Making in Power Systems Wide-Area Protection

Creator:

Meier, Richard John

Abstract:

In recent years there have been many improvements in the reliability of critical infrastructure systems. Despite these improvements and despite targeted efforts to improve the operation and control of the electric grid, the power systems industry has seen relatively small advances in this regard. For instance, today's power system is...

Resource Type:

Masters Thesis

Full Text:

Wide-Area Protection AN ABSTRACT OF THE THESIS OF Richard John Meier for the degree of Master of
Deep Segmentation in Plant Phenomics

Creator:

Kaur, Damanpreet

Abstract:

The abilities of plant biologists to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation and mainly to collect this data on a high-throughput scale at low cost. Deep learning-based methods have demonstrated unprecedented potential to automate...

Resource Type:

Masters Thesis
UCT for tactical assault battles in real-time strategy games

Creator:

Balla, Radha-Krishna

Abstract:

We consider the problem of tactical assault planning in real-time strategy games where a team of friendly agents must launch an assault on an enemy. This problem offers many challenges including a highly dynamic and uncertain environment, multiple agents, durative actions, numeric attributes, and different optimization objectives. While the dynamics...

Resource Type:

Masters Thesis
Information-theoretic Approach to Design and Evaluate Privacy-preserving and Fair Frameworks for Continuous High-dimensional Data

Creator:

Alsulaimawi, Zahir Ahmed Hussein

Abstract:

Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them. Further, there have been concerns about the possibility of bias and discrimination in predictive applications. In order to address these issues, we propose an...

Resource Type:

Dissertation
Bayesian methods for knowledge transfer and policy search in reinforcement learning

Creator:

Wilson, Aaron

Abstract:

How can an agent generalize its knowledge to new circumstances? To learn effectively an agent acting in a sequential decision problem must make intelligent action selection choices based on its available knowledge. This dissertation focuses on Bayesian methods of representing learned knowledge and develops novel algorithms that exploit the represented...

Resource Type:

Dissertation
Simulator-Defined MDP Planning with Applications in Natural Resource Management

Creator:

Alkaee Taleghan, Majid

Abstract:

This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...

Resource Type:

Dissertation
Structured learning with latent variables : theory and algorithms

Creator:

Zhao, Kai

Abstract:

Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...

Resource Type:

Dissertation
Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

Creator:

Seo, Eugene

Abstract:

Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...

Resource Type:

Dissertation
Efficient training and feature induction in sequential supervised learning

Creator:

Hao, Guohua

Abstract:

Sequential supervised learning problems arise in many real applications. This dissertation focuses on two important research directions in sequential supervised learning: efficient training and feature induction. In the direction of efficient training, we study the training of conditional random fields (CRFs), which provide a flexible and powerful model for sequential...

Resource Type:

Dissertation

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Academic Affiliation

Electrical Engineering and Computer Science[remove]16

Advisor

Tadepalli, Prasad4
Dietterich, Thomas G.3
Fern, Alan3
Burnett, Margaret M.1
Cotilla Sanchez, Eduardo1
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Commencement Year

Commencement Year range begin – Commencement Year range end

Current results range from 2006 to 2022

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Committee Member

Fern, Alan5
Tadepalli, Prasad5
Niess, Margaret3
Wong, Weng-Keen3
Cull, Paul2
more Committee Members »

Creator

Alkaee Taleghan, Majid1
Alsulaimawi, Zahir Ahmed Hussein1
Balla, Radha Krishna1
Bjarnason, Ronald V.1
Dodge, Jonathan E.1
more Creators »

Contributor

Clarke, Justin1
Fu, Xiao1
Hallman, Tyler A.1
Hutchinson, Rebecca A.1
Kilbride, John1
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Date

Date range begin – Date range end

Current results range from 2005 to 2022

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Decade

2020-20296
2010-20195
2000-20095

Degree Field

Computer Science13
Electrical and Computer Engineering3

Degree Level

Doctoral12
Master's4

Degree Name

Doctor of Philosophy (Ph.D.)12
Master of Science (M.S.)4

File Format

application/pdf2

Language

English [eng]16

License

All rights reserved16

Non-Academic Affiliation

Oregon State University. Graduate School10

Peer Reviewed

No16

Resource Type

Dissertation12
Masters Thesis4

Rights Statement

In Copyright[remove]16

Subject

Machine learning2
Markov processes2
Reinforcement learning2
Artificial intelligence -- Mathematical models1
Bayesian statistical decision theory1
more Subjects »

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