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Spring 2011

Yang, Fan

In this thesis, we study theoretically and empirically the additive abstraction-based heuristics. First we present formal general definitions for abstractions that extend to general additive abstractions. We show that the general definition makes proofs of admissibility, consistency, and...

Spring 2019

Liu, Chang

With the burgeoning of online social media and the deluge of information in today's "big data" era, traditional community mining that relies on the connections of the nodes no longer suffices to find communities where the attributes of these nodes play an important role. Though vast research has...

Fall 2009

Jocksch, Adam

This thesis introduces FlowGSP, a general-purpose sequence mining algorithm for flow graphs. FlowGSP ranks sequences according to the frequency with which they occur and according to their relative cost. This thesis also presents two parallel implementations of FlowGSP. The first implementation...

Fall 2009

Patterson, Jordan

Problems in scientific computing often consist of a workload of jobs with dependencies between them. Batch schedulers are job-oriented, and are not well-suited to executing these workloads with complex dependencies. We introduce Jole, a Python library created to run these workloads. Jole has...

Spring 2015

White, Martha

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...

Fall 2023

Chui, Daniel CY

Modelling agent preferences has applications in a range of fields including economics and increasingly, artificial intelligence. These preferences are not always known and thus may need to be estimated from observed behavior, in which case a model is required to map agent preferences to...

Fall 2021

Ata-E-Rabbi, H M

The appearance of an image projected by a projector onto an arbitrary surface has the potential to appear differently depending on several factors, e.g., the properties of the surface being projected on, the colors of the light projected by the projector and the colors and the optical properties...

Spring 2022

Aghaei, Nikoo

Data augmentation is a strong tool for enhancing the performance of deep learning models using different techniques to increase both the quantity and diversity of training data. Cutout was previously proposed, in the context of image classification, as a simple regularization technique that...

2005

Pireddu, Luca

Fall 2015

Roy, Ankush

Object tracking is a much researched subject in the computer vision community. With more and more tracking algorithms reported every year, standard benchmarking and evaluation methods are reported for long term tracking systems. We present a public dataset to evaluate trackers used for human and...