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- 26Artificial Intelligence
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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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Scalable Solutions to Image Abnormality Detection and Restoration using Limited Contextual Information
DownloadFall 2020
Detecting and interpreting image abnormalities and restoring images are essential to many processing pipelines in diverse fields. Challenges involved include randomness and unstructured nature of image artefacts (from signal processing perspective) and performance constraints imposed by...
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Fall 2017
Real-time strategy (RTS) games are war simulation video games in which the players perform several simultaneous tasks like gathering and spending resources, building a base, and controlling units in combat against an enemy force. RTS games have recently drawn the interest of the game AI research...
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Fall 2018
Neural approaches to sequence labeling often use a Conditional Random Field (CRF) to model their output dependencies, while Recurrent Neural Networks (RNN) are used for the same purpose in other tasks. We set out to establish RNNs as an attractive alternative to CRFs for sequence labeling. To do...
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Solving Witness-type Triangle Puzzles Faster with an Automatically Learned Human-Explainable Predicate
DownloadFall 2023
The Witness is a game with difficult combinatorial puzzles that are challenging for both human players and artificial intelligence based solvers. Indeed, the number of candidate solution paths to the largest puzzle considered in this thesis is on the order of 10^(15) and search-based solvers can...
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Spring 2024
In reinforcement learning, the notion of state plays a central role. A reinforcement learning agent requires the state to evaluate its current situation, select actions, and construct a model of the environment. In the classic setting, it is assumed that the environment provides the agent with...
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Fall 2014
Designing competitive Artificial Intelligence (AI) systems for Real-Time Strategy (RTS) games often requires a large amount of expert knowledge (resulting in hard-coded rules for the AI system to follow). However, aspects of an RTS agent can be learned from human replay data. In this thesis, we...
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Statistical Learning with Many Variables as Covariates or Outcomes: Association Inference and Prediction of Late effects of Childhood Cancer and Its Treatment
DownloadSpring 2024
Advancements in childhood cancer treatment have increased the 5-year survival rates substantially, from 20% in 1950-1954 to over 85% currently. While this success is a remarkable accomplishment in oncology, it concurrently introduces a new concern, namely, the emergence of late adverse effects,...
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Strange springs in many dimensions: how parametric resonance can explain divergence under covariate shift.
DownloadFall 2021
Most convergence guarantees for stochastic gradient descent with momentum (SGDm) rely on independently and identically ditributed (iid) data sampling. Yet, SGDm is often used outside this regime, in settings with temporally correlated inputs such as continual learning and reinforcement learning....
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Fall 2023
The evolution of cloud computing in the last decade has offered unprecedented access to sizable, configurable computing resources with minimal management effort. Containerization of applications, particularly through Docker, has been pivotal in this progression. As modern software increasingly...