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Skip to Search Results- 36Machine learning
- 7Online learning
- 5Artificial intelligence
- 3Game theory
- 3Reinforcement learning
- 2Fmri
- 2White, Martha
- 1Ajallooeian, Mohammad Mahdi
- 1Allen, Felicity R
- 1Bard, Nolan DC
- 1Bartók, Gábor
- 1Bastani, Meysam
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Machine learning classification of plant genotypes grown under different light conditions through the integration of multi-scale time-series data
DownloadFall 2023
In order to mitigate the effects of a changing climate, agriculture requires more effective evaluation, selection, and production of crop cultivars in order to accelerate genotype-to-phenotype connections and the selection of beneficial traits. Critically, plant growth and development are highly...
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Fall 2012
This thesis provides a description of the cardiac rhythm as a latent chain of heart sound arrivals which occur over time, where each arrival generates a fixed window of observable data that can be described with arbitrary feature functions. This description of the process produces tractable...
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Spring 2014
Each patient with Type-1 diabetes must decide how much insulin to inject before each meal to maintain an acceptable level of blood glucose. The actual injection dose is based on a formula that takes current blood glucose level and the meal size into consideration. While following this insulin...
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Spring 2016
Ideal agent behaviour in multiagent environments depends on the behaviour of other agents. Consequently, acting to maximize utility is challenging since an agent must gather and exploit knowledge about how the other (potentially adaptive) agents behave. In this thesis, we investigate how an...
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Fall 2016
In an online learning problem a player makes decisions in a sequential manner. In each round, the player receives some reward that depends on his action and an outcome generated by the environment while some feedback information about the outcome is revealed. The goal of the player can be...
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Spring 2022
In this dissertation, we study online off-policy temporal-difference learning algorithms, a class of reinforcement learning algorithms that can learn predictions in an efficient and scalable manner. The contributions of this dissertation are one of the two kinds: (1) empirically studying existing...
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Optimal Mechanisms for Machine Learning: A Game-Theoretic Approach to Designing Machine Learning Competitions
DownloadSpring 2013
In this thesis we consider problems where a self-interested entity, called the principal, has private access to some data that she wishes to use to solve a prediction problem by outsourcing the development of the predictor to some other parties. Assuming the principal, who needs the machine...
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Fall 2014
In the face of an overwhelmingly information intensive Internet, searching has become the most important way to locate information efficiently. Current searching techniques are able to retrieve relevant data, however, personalization techniques are still needed to better identify different user...
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Fall 2015
Polarity classification in text is the problem of automatically detecting the general opinion of textual data. Analyzing the general opinion toward a topic of interest is important for different audiences, such as companies, politicians or even regular users. On the other hand, the availability of...
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Fall 2009
Understanding biochemical reactions inside cells of individual organisms is a key factor for improving our biological knowledge. Signaling pathways provide a road map for a wide range of these chemical reactions that convert one signal or stimulus into another. In general, each signaling pathway...