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Spring 2021

Wen, Junfeng

This dissertation demonstrates how to utilize data collected previously from different sources to facilitate learning and inference for a target task. Learning from scratch for a target task or environment can be expensive and time-consuming. To address this problem, we make three contributions...

Spring 2021

Faraji, Mehdi

Active sensors, such as active cameras and ultrasound transducers, are becoming more popular. One particular type of active camera, the Pan-Tilt-Zoom (PTZ) camera, has become ubiquitous in surveillance platforms. Given their active nature, active cameras are omnipresent in robotic systems as...

Spring 2021

Linke, Cameron

Learning about many things can provide numerous benefits to a reinforcement learning system. For example, learning many auxiliary value functions, in addition to optimizing the environmental reward, appears to improve both exploration and representation learning. The question we tackle in this...

Spring 2021

Ni, Jingjiao

Emphatic-Temporal-Difference (Emphatic-TD) learning algorithms were recently proposed based on the most central and widely used reinforcement learning algorithms, Temporal-Difference (TD) methods. Emphatic-TD learning algorithms were originally designed to solve the divergence problem of...

Fall 2021

Kuzma, Braedy

General Matrix-Matrix Multiplication (GEMM) is used widely in many high-performance application domains. In many cases, these applications repeatedly execute their matrix-multiplication subroutine, as is the case in the implementation of a particle-physics simulator or the repeated convolutions...

Fall 2021

Nuryyev, Batyr

Application Programming Interfaces (APIs) allow developers to reuse existing functionality without knowing the implementation details. However, developers might make mistakes in using APIs, which are known as API misuses. One way to detect and prevent API misuses is to encode usage specifications...

Fall 2021

Yang, Yuchen

Deep neural network (DNN) has been developed rapidly in years. While it shows promising results in various tasks of computer vision, DNN typically suffers from accuracy loss due to the domain shift from a source domain to a target domain. To mitigate the accuracy loss without the label from...

Fall 2021

Hasnat, Md Arif

We study the problem of set discovery where given a few example tuples of a desired set, we want to find the set in a collection of sets. A challenge is that the example tuples may not uniquely identify a set, and a large number of candidate sets may be returned. Our focus is on interactive...

Fall 2021

Hashemzadeh, Maryam

The representations generated by many models of language (word embeddings, recurrent neural networks and transformers) correlate to brain activity recorded while people listen. However, these decoding results are usually based on the brain’s reaction to syntactically and semantically sound...

Spring 2021

Wong, Andy

This thesis investigates the use of general value functions for detecting anomalous behavior in machines. Identifying abnormal behavior is critical for ensuring the safety and reliability of any machine or industrial process. When the cause of these anomalies is due to accumulated wear on...