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Spring 2024

Rafiee, Banafsheh

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...

Fall 2014

Erickson, Graham KS

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...

Fall 2021

Banman, Kirby

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....

Spring 2018

Borle, Neil C

Patients with Type I Diabetes (T1D) must take insulin injections to prevent the serious long term effects of hyperglycemia – high blood glucose (BG). These patients must also be careful not to inject too much insulin because this could induce hypoglycemia (low BG), which can be fatal. Patients...

Fall 2024

Fahim, Abrar

Learning jointly from images and texts using contrastive pre-training has emerged as an effective method to train large-scale models with a strong grasp of semantic image concepts. For instance, CLIP, pre-trained on a large corpus of web data, excels in tasks like zero-shot image classification,...

Fall 2020

Shibhansh Dohare

We explore the interplay of generate-and-test and gradient-descent techniques for solving online supervised learning problems. The task in supervised learning is to learn a function using samples of inputs to output pairs. This function is called the target function. The standard way to learn...

Fall 2019

Diaz Romero, Dillam Jossue

The Smart Condo is a model condo embedded with a wireless sensor network, developed by an interdisciplinary team including researchers from Occupational Therapy, Industrial Design, Pharmacy, and Computing Science. The Smart Condo aims to support older adults, including those with physical and...

Spring 2023

Jadhav, Mrunal Sunil

Procedural Level Generation via Machine Learning (PLGML) refers to the application of machine learning techniques to the automated generation of game levels. PLGML researchers have investigated different level generation techniques to generate new game levels matching the style of a training...

Spring 2017

Ávila Pires, Bernardo

In this dissertation, we advance the theoretical understanding of two families of Reinforcement Learning (RL) methods: Classification-based policy iteration (CBPI) and model-based reinforcement learning (MBRL) with factored semi-linear models. In contrast to generalized policy iteration, CBPI...

Spring 2023

Dziri, Nouha

Dialogue systems powered by large pre-trained language models exhibit an innate ability to deliver fluent and natural-sounding responses. Despite their impressive performance, these models fail to conduct interesting and consistent exchanges of turns and can often generate factually incorrect...