Index Catalog // ScholarsArchive@OSU

A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

Creator:: Emmott, Andrew F.
Abstract:: It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
Resource Type:: Masters Thesis

Knowledge Base Completion Leveraging Natural Language Data

Creator:: Shahbazi, Hamed
Abstract:: Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
Resource Type:: Dissertation

Analytical Methods for Improving Causal Inference

Creator:: Sinha, Meghamala
Abstract:: Causal inference is an important analytical tool to bridge the gap between prediction and decision-making. However, learning a causal network solely from data is a challenging task. In this work, various techniques have been explored for a better and improved causal network learning from data. Firstly, the problem of learning...
Resource Type:: Dissertation

Improving and Understanding Deep Models for Natural Language Comprehension

Creator:: Ghaeini, Reza
Abstract:: Natural Language Comprehension is a challenging domain of Natural Language Processing. To improve a model’s language comprehension/understanding, one approach would be to enrich the structure of the model to enhance its capability in learning the latent rules of the language. In this dissertation, we will ﬁrst introduce several deep models...
Resource Type:: Dissertation

Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

Creator:: Dodge, Jonathan E.
Abstract:: Assessing AI systems is difficult. Humans rely on AI systems in increasing ways, both visible and invisible, meaning a variety of stakeholders need a variety of assessment tools (e.g., a professional auditor, a developer, and an end user all have different needs). We posit that it is possible to provide...
Resource Type:: Dissertation

An Information Modeling Framework for Support of Sustainable Manufacturing System Design Decision Making

Creator:: Shankar Raman, Arvind
Abstract:: Manufacturing technology has continuously evolved and advanced over the past century; this has led to an increase in the production of consumer and industrial goods driven by simultaneous growth in population and wealth. Despite the resulting economic and labor growth, environmental impacts of manufacturing have increased dramatically due to the...
Resource Type:: Dissertation

Advances in Simultaneous Translation

Creator:: Zheng, Renjie
Abstract:: Simultaneous translation, which translates concurrently with the source language speech, is widely used in many scenarios including multilateral organizations. However, it is well known to be one of the most challenging tasks for humans due to the simultaneous perception and production in two languages. On the other hand, simultaneous translation...
Resource Type:: Dissertation
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Investigating Latent State and Uncertainty Representations in Reinforcement Learning

Creator:: Koul, Anurag
Abstract:: Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
Resource Type:: Dissertation

A General Purpose Agent-Based Blackboard Optimization Method Applied to Sodium Fast Reactor Design and Analysis

Creator:: Stewart, Ryan H.
Abstract:: We present a novel multi-objective optimization methodology built upon a multi-agent blackboard framework. This multi-agent blackboard system (MABS) synthesizes blackboard architectures, multi-agent environments, and optimization theory. The blackboard architecture creates the framework for initializing, storing, and solving a multi-objective optimization problem. Multiple agents allow for an optimization problem to be...
Resource Type:: Dissertation

Coordination for Scalable Multiple Robot Planning Under Temporal Uncertainty

Creator:: Marcon dos Santos, Gilberto
Abstract:: This dissertation incorporates coalition formation and probabilistic planning towards a domain-independent automated planning solution scalable to multiple heterogeneous robots in complex domains. The first research direction investigates the effectiveness of Task Fusion and introduces heuristics that improve task allocation and result in better quality plans, while requiring lower computational cost...
Resource Type:: Dissertation

ScholarsArchive@OSU

A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

Knowledge Base Completion Leveraging Natural Language Data

Analytical Methods for Improving Causal Inference

Improving and Understanding Deep Models for Natural Language Comprehension

Explanations and Processes to Enable Humans to Assess AI with Respect to Manipulable Properties

An Information Modeling Framework for Support of Sustainable Manufacturing System Design Decision Making

Advances in Simultaneous Translation

Investigating Latent State and Uncertainty Representations in Reinforcement Learning

A General Purpose Agent-Based Blackboard Optimization Method Applied to Sodium Fast Reactor Design and Analysis

Coordination for Scalable Multiple Robot Planning Under Temporal Uncertainty

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