Index Catalog // ScholarsArchive@OSU

Model Selection of Discrete Classifiers under Class and Cost Distribution Change: An Empirical Study

Creator:: Ahmed, Nahian and Hutchinson, Rebecca A.
Abstract:: A variety of important machine learning applications require predictions on test data with different characteristics than the data on which a model was trained and validated. In particular, test data may have a different relative frequency of positives and negatives (i.e., class distribution) and/or different mislabeling costs of false positive...
Resource Type:: Technical Report
Full Text:: . Model selection as a threshold choice problem based on expected loss/cost has been studied by Hernández

Relational Learning over Dirty Data Using Data Constraints

Creator:: Lee, Ga Young
Abstract:: Real-world datasets are dirty and contain many errors. Examples of these issues are violations of integrity constraints, duplicates, and inconsistencies in representing data values and entities. Applying machine learning on dirty databases may lead to inaccurate results. Users have to spend a lot of time and effort repairing data errors...
Resource Type:: Masters Thesis

Low-power double-sampled delta-sigma modulator for broadband applications

Creator:: Shen, Weilun
Abstract:: High speed and high resolution analog-to-digital converter is a key building block for broadband wireless communications, high definition video applications, medical images and so on. By leveraging the down scaling of the latest CMOS technology and the noise shaping properties, delta-sigma (ΔΣ) ADCs are able to achieve wide-band operation and...
Resource Type:: Dissertation
Full Text:: Victor Fong, my circuit and layout design ability is able to be brought to a completely new level. I

Growth and characterization of zinc ferrite thin films for high frequency applications

Creator:: Hu, Jiqing
Abstract:: Ferrites have been used for various high frequency applications as bulk materials. These applications, however, are limited to large dimension devices. In this thesis, thin film ferrites were deposited from a low temperature solution-based deposition process that is suitable for micro-scale high frequency applications. The low temperature nature of this...
Resource Type:: Dissertation

The Symbioses of Oblivious Random Access Memory and Trusted Execution Environments

Creator:: Rahal-Arabi, Hadi
Abstract:: In recent years, Oblivious Random Access Memory (ORAM) controllers in Trusted Execution Environments (TEEs) have become a popular area of investigation, as coresident trusted systems allow for significantly more efficient oblivious execution. Further, in the case of Intel architectures, oblivious execution effectively eliminates the majority of confidentiality leakage holes in...
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

Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

Creator:: Zemicheal, Tadesse H.
Abstract:: Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
Resource Type:: Dissertation

Quantum dot plasmon coupling : Fundamental study and applications

Creator:: Kannegulla, Akash
Abstract:: The dissertation focuses on the engineering of light-matter interaction using plasmonic nanoparticles and metamaterials to achieve enhanced luminescence and based on which to improve the performance of biosensing and light-emitting technologies. We designed and fabricated a spectrum of nanostructures to exhibit particular dispersion relations capable of controlling the spontaneous emission...
Resource Type:: Dissertation

Representationally Robust and Scalable Learning over Relational Databases

Creator:: Picado Leiva, Jose Manuel
Abstract:: Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the...
Resource Type:: Dissertation

Algorithms for massive biological datasets

Creator:: Bryant, Douglas W. (Douglas Wesley)
Abstract:: Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
Resource Type:: Dissertation

ScholarsArchive@OSU

Model Selection of Discrete Classifiers under Class and Cost Distribution Change: An Empirical Study

Relational Learning over Dirty Data Using Data Constraints

Low-power double-sampled delta-sigma modulator for broadband applications

Growth and characterization of zinc ferrite thin films for high frequency applications

The Symbioses of Oblivious Random Access Memory and Trusted Execution Environments

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

Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

Quantum dot plasmon coupling : Fundamental study and applications

Representationally Robust and Scalable Learning over Relational Databases

Algorithms for massive biological datasets

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