Index Catalog // ScholarsArchive@OSU

Improving the Quality of Software Using Mutation Testing and Fault Prediction

Creator:: Ahmed, Iftekhar
Abstract:: Our confidence in software systems depends on our confidence in the exhaustiveness of our testing. As software systems get more complex, the task of exhaustive testing becomes more complex and even infeasible in some cases. In order to build less error prone systems, we therefore need to not only focus...
Resource Type:: Dissertation
Full Text:: provided special guidance and mentorship during my time here. Alex Groce, Anita Sarma, and Margaret M

Network Coding, Random Matrices, and Their Applications to Communication Systems

Creator:: Nguyen-Huu, Duong
Abstract:: In this work, we study network coding technique, its relation to random matrices, and their applications to communication systems. The dissertation consists of three main contributions. First, we propose efficient algorithms for data synchronization via a broadcast channel using random network coding. Second, we study the resiliency of network coding...
Resource Type:: Dissertation

Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

Creator:: Shrestha, Sagar
Abstract:: Transmit beamforming is an important technique employed to improve efficiency and signal quality in wireless communication systems by steering signals towards their in- tended users. It often arises jointly with the antenna selection problem due to various reasons, such as limited number of radio frequency (RF) chains and energy/resource effi-...
Resource Type:: Masters Thesis

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

Large Scale Tensor Decomposition Algorithms Using Block-randomized Stochastic Proximal Gradient

Creator:: Gao, Cheng
Abstract:: We consider the problem of computing the cannonical polyadic decomposition (CPD) for large-scale dense tensors. This work is a combination of alternating least squares and fiber sampling. Data sparsity can be leveraged to handle large tensor CPD, but this route is not feasible for dense data. Inspired by stochastic optimization's...
Resource Type:: Masters Thesis

Towards Direct Simultaneous Speech Translation

Creator:: Chen, Junkun
Abstract:: Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
Resource Type:: Dissertation

Efficient Spectrum Sensing and Sharing Techniques for Dynamic Wideband Spectrum Access

Creator:: Khalfi, Bassem
Abstract:: Besides enabling an enhanced mobile broadband access, fifth-generation (5G) wireless mobile networks are envisioned to support the connectivity of massive, heterogeneous Internet of Things (IoT) devices. Connecting these devices through 5G systems and providing them with their needed data rates require huge amounts of spectrum and power resources, thus calling...
Resource Type:: Dissertation

Surface-Normal Modulation of Fano Resonances in Metallic Photonic Crystals for Free-Space Optical Interconnects

Creator:: Ren, Fanghui
Abstract:: This dissertation focuses on the development of ultra-compact optical devices for free-space modulation. We propose a surface-normal modulator using metallic photonic crystals for free-space optical interconnects. The active control of light intensity is achieved by engineering the Fano resonances in metallic photonic crystals. Both thermo-optic modulation and electro-optic modulation of...
Resource Type:: Dissertation

Improving automated email tagging with implicit feedback

Creator:: Sorower, Mohammad Shahed
Abstract:: Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
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

ScholarsArchive@OSU

Improving the Quality of Software Using Mutation Testing and Fault Prediction

Network Coding, Random Matrices, and Their Applications to Communication Systems

Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

Advances in Simultaneous Translation

Large Scale Tensor Decomposition Algorithms Using Block-randomized Stochastic Proximal Gradient

Towards Direct Simultaneous Speech Translation

Efficient Spectrum Sensing and Sharing Techniques for Dynamic Wideband Spectrum Access

Surface-Normal Modulation of Fano Resonances in Metallic Photonic Crystals for Free-Space Optical Interconnects

Improving automated email tagging with implicit feedback

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

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