Index Catalog // ScholarsArchive@OSU

Semantic embodied navigation : developing agents that navigate from language and vision

Creator:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation

Hierarchical graphical models for activity recognition in videos

Creator:: Amer, Mohamed R.
Abstract:: This dissertation addresses the problem of recognizing human activities in videos. Our focus is on activities with stochastic structure, where the activities are characterized by variable space-time arrangements of actions, and conducted by a variable number of actors. These activities occur frequently in sports and surveillance videos. They may appear...
Resource Type:: Dissertation

Decentralized Multi-Robot Exploration with Sparse Communication through Deep Imitation Learning

Creator:: Senewiratne, Yomal K.
Abstract:: We present a method for decentralized, multi-robot exploration in adverse environments where communication is minimal. A key conceptual feature of our method is enabling implicit coordination between robots by training a Convolutional Neural Network (CNN) as a heuristic for planning using Monte Carlo Tree Search (MCTS). Our method consists of...
Resource Type:: Masters Thesis

The density signature

Creator:: Migler-VonDollen, Theresa
Abstract:: In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
Resource Type:: Dissertation

Theory and Implementation of a Variational Database Management System

Creator:: Ataei, Parisa S.
Abstract:: In this thesis, I present the variational database management system, a formal framework and its implementation for representing variation in relational databases and managing variational information needs. A variational database is intended to support any kind of variation in a database. Specific kinds of variation in databases have already been...
Resource Type:: Dissertation
Full Text:: drive! And thank you to Jose Calderson for honest open conversations on building a research career. He

Learning to Estimate Multi-Relation Aggregation Functions

Creator:: Jadhav, Rashmi Suresh
Abstract:: Multi-relation aggregation queries process the join operator before computing the aggregation function. This join is arguably the most costly operation since traditional join algorithms spend majority of their time trying to join the parts of the relations that do not generate any output tuples. This causes slow response times with...
Resource Type:: Masters Thesis

Methods for Detection and Recovery of Out-of-Distribution Examples

Creator:: Ratzlaff, Neale J.
Abstract:: Deep neural networks currently comprise the backbone of many applications where safety is a critical concern, for example: autonomous driving and medical diagnostics. Unfortunately these systems currently fail to detect out-of-distribution (OOD) inputs and can be prone to making dangerous errors when exposed to them. In addition, these same systems...
Resource Type:: Masters Thesis

Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

Creator:: Khorram, Saeed
Abstract:: The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
Resource Type:: Dissertation

Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

Creator:: Khorram, Saeed
Abstract:: In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
Resource Type:: Masters Thesis

Statistical Properties and Guarantees for Certain Anomaly Detection Relevant Problems

Creator:: Liu, Si
Abstract:: Anomaly detection aims at detecting the points that appear different than the majority of the data, such that they are suspected to be generated from a different distribution. Anomaly detectors have been applied in many different fields, such as detecting fraudulent behaviors in bank transaction, finding broken sensors in a...
Resource Type:: Dissertation

ScholarsArchive@OSU

Semantic embodied navigation : developing agents that navigate from language and vision

Hierarchical graphical models for activity recognition in videos

Decentralized Multi-Robot Exploration with Sparse Communication through Deep Imitation Learning

The density signature

Theory and Implementation of a Variational Database Management System

Learning to Estimate Multi-Relation Aggregation Functions

Methods for Detection and Recovery of Out-of-Distribution Examples

Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

Statistical Properties and Guarantees for Certain Anomaly Detection Relevant Problems

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