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Skip to Search Results- 29Greiner, Russell (Computing Science)
- 21Bowling, Michael (Computing Science)
- 14Schuurmans, Dale (Computing Science)
- 6Szepesvari, Csaba (Computing Science)
- 2White, Martha (Computing Science)
- 1Bellemare, Marc (Google Brain)
- 14Machine learning
- 13Machine Learning
- 9Reinforcement Learning
- 7Artificial Intelligence
- 3Game Theory
- 2Abstractions
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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...
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Fall 2009
This thesis addresses the challenge of prognosis, in terms of survival prediction, for patients with Glioblastoma Multiforme brain tumors. Glioblastoma is the most malignant brain tumor, which has a median survival time of no more than a year. Accurate assessment of prognostic factors is critical...
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Spring 2015
This dissertation explores regularized factor models as a simple unification of machine learn- ing problems, with a focus on algorithmic development within this known formalism. The main contributions are (1) the development of generic, efficient algorithms for a subclass of regularized...
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Fall 2013
Many learning situations involve learning the conditional distribution $p(y|x)$ when the training data is drawn from the training distribution $p{tr}(x)$, even though it will later be used to predict for instances drawn from a different test distribution $p{te}(x)$. Most current approaches focus...
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Spring 2016
Games have been used as a testbed for artificial intelligence research since the earliest conceptions of computing itself. The twin goals of defeating human professional players at games, and of solving games outright by creating an optimal computer agent, have helped to drive practical ...
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Spring 2017
Co-embedding is the process of mapping elements from multiple sets into a common latent space, which can be exploited to infer element-wise associations by considering the geometric proximity of their embeddings. Such an approach underlies the state of the art for link prediction, relation...
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Spring 2017
Survival prediction is becoming a crucial part of treatment planning for most terminally ill patients. Many believe that genomic data will enable us to better estimate survival of these patients, which will lead to better, more personalized treatment options and patient care. As standard...
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Spring 2023
AlphaZero is a self-play reinforcement learning algorithm that achieves superhuman play in the games of chess, shogi, and Go via policy iteration. To be an effective policy improvement operator, AlphaZero’s search needs to have accurate value estimates for the states that appear in its search...
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Fall 2013
Given nothing but the generative model of the environment, Monte Carlo Tree Search techniques have recently shown spectacular results on domains previously thought to be intractable. In this thesis we try to develop generic techniques for temporal abstraction inside MCTS that would allow the...
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Spring 2014
Efficient, unbiased estimation of agent performance is essential for drawing statistically significant conclusions in multi-agent domains with high outcome variance. Naive Monte Carlo estimation is often insufficient, as it can require a prohibitive number of samples, especially when evaluating...