Index Catalog // ScholarsArchive@OSU

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

Creator:: Nelson, Aiden J.
Abstract:: University students first learning about computer science (CS) can be intimidated and frustrated by programming. In addition, the general-purpose programming languages chosen for introducing students to programming contain several features that have the potential to overwhelm and distract them from focused curriculum topics, which can lead to reduced retention of...
Resource Type:: Masters Thesis

Creator:: Li, Yunfan
Abstract:: The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
Resource Type:: Dissertation

Creator:: Aziere, Nicolas
Abstract:: This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Resource Type:: Dissertation

Creator:: Rajabi, Arezoo
Abstract:: Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
Resource Type:: Dissertation

ScholarsArchive@OSU