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Not stated in source 2024 Needs review

Explorations of In-Context Reinforcement Learning

Author
Ethan Brooks
University
University of Michigan
Country
United States
Main specialisation
Natural Language Processing › Large Language Models

In-Context Learning describes a form of learning that occurs when a model accumulates information in its context or memory. For example, a Long Short-Term Memory unit (LSTM) can rapidly adapt to a novel task as input/target exemplars are fed into it. While in-…

Not stated in source 2024 Needs review

Language Supervision for Computer Vision

Author
Karan Desai
University
University of Michigan
Country
United States
Main specialisation
Natural Language Processing › Large Language Models

Representation learning lies at the core of modern Artificial Intelligence. In computer vision, labeled image datasets like ImageNet have been the standard choice for representation learning. Despite being empirically successful, this approach is expensive to…

Not stated in source 2022 Needs review

Design and Implementation of an Autonomous Driving System with a Deep Learning Approach on a Scaled Vehicle Platform

Author
Jesudara Omidokum
University
University of Michigan
Country
United States
Main specialisation
Deep Learning & Neural Networks › AI in Education

The thesis project is developed to create a platform for autonomous driving research and education purposes. The main goal of this study is to present a complete and adequate way for building a platform with a drive-by-wire system and sensor packages that are…

Not stated in source 2022 Needs review

Discovery in Reinforcement Learning

Author
Vivek Veeriah
University
University of Michigan
Country
United States
Main specialisation
Computer Vision › Predictive Analytics & Time Series

This thesis focuses on Reinforcement Learning (RL) which considers an agent that makes sequen- tial decisions in an environment to maximize its reward. Recent breakthroughs on domains such as Go, Atari games, and Robotics are a result of combining advances fro…

Not stated in source 2021 Needs review

Deep Learning Approaches for Condition Monitoring and Prognostic Analysis

Author
Zunya Shi
University
University of Michigan
Country
United States
Main specialisation
AI in Healthcare › Predictive Analytics & Time Series

Predictive analytics is a technique to make predictions about future unknown events by analyzing current and historical data. The market for predictive analysis is expected to reach $12.4 billion in 2022. Prognostic analysis is one dimension of predictive anal…

Not stated in source 2020 Needs review Available

Demographic-Aware Natural Language Processing

Author
Aparna Garimella
University
University of Michigan
Country
United States
Main specialisation
Natural Language Processing › Speech Recognition

The underlying traits of our demographic group affect and shape our thoughts, and therefore surface in the way we express ourselves and employ language in our day-to-day life. Understanding and analyzing language use in people from different demographic backgr…

Not stated in source 2019 Needs review Available

Artificial Intelligence and Cybersecurity: Building an Automotive Cybersecurity Framework Using Machine Learning Algorithms

Author
Nevrus Kaja
University
University of Michigan
Country
United States
Main specialisation
Responsible AI › Fairness, Privacy & Ethics

Automotive technology has continued to advance in many aspects. As an outcome of such advancements, autonomous vehicles are closer to commercialization and have brought to life a complex automotive technology ecosystem [1]. Like every other technology, these d…

Not stated in source 2017 Needs review

Deep Learning and Reward Design for Reinforcement Learning

Author
Xiaoxiao Guo
University
University of Michigan
Country
United States
Main specialisation
Natural Language Processing › Convolutional Neural Networks

One of the fundamental problems in Artificial Intelligence is sequential decision making in a flexible environment. Reinforcement Learning (RL) gives a set of tools for solving sequential decision problems. Although the theory of RL addresses a general class o…