Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 160 for “"Multi-task"”.
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Preventive Maintenance for a Multi-task System
This research models the behavior of a multi-task system with respect to time. The type of multi-task system considered here is one in which not all system components are required to perform each task. Each component may, however, be used for more than one task. Also, it is possible that some of …
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Human operator performance in dynamic multi-task environments
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1988.
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Efficient Continuous Pareto Exploration in Multi-Task Learning
Tasks in multi-task learning often correlate, conflict, or even compete with each other. As a result, a single solution that is optimal for all tasks rarely exists. Recent papers introduced the concept of Pareto optimality to this field and directly cast multi-task learning as multiobjective …
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DEEP MULTI-TASK LEARNING FOR FACE AND HUMAN ANALYSIS
In this thesis, we use multi-task learning methods to solve face and human analysis tasks. We design multi-task learning models to learn multiple face and human analysis tasks. We demonstrate that deep multi-task learning can be used to perform the face attribute classification task and up to 40 …
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Integrating Imperfect Automated Aids Into a Multi -Task Situations
… particular events or situations during complex tasks. Automated aids can be useful by taking over a function once performed by the human thereby freeing up the person to do other tasks. However, automated aids may also introduce costs to task performance that are not readily apparent. In four …
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AdaTAD - a debugger for the Ada multi-task environment
… that it supports concurrent programming via its "task" compilation unit. There are not, however, any automated tools to aid in locating errors in the tasks. The design for such a tool is presented. The tool is named AdaTAD and is a debugger for programs written in Ada. The features of AdaTAD are …
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Multi-triage: A Multi-Task Learning Approach to Bug Triaging
… the effectiveness of linkages between two triage tasks. An automated approach to assisting the issue allocation process to relevant category and developer benefits bug triages. A large body of previous work aims to address the allocation problem by conjecturing the extensive list of approaches …
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Toward time-predictable execution of multi-task real-time systems
… be sources of significant unpredictability in task executions if they are not operated in a deterministic manner. In particular, our analysis and experiments in [6, 35] show that with the standard cache and memory controller sharing mechanism, the execution time of a task may be unpredictably …
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Subjective scaling of mental workload in a multi-task environment
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1980.
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Learning Heterogeneous Resource-Constrained Task Allocation Using Concurrent Multi-Task Bandits
Task allocation is a critical aspect of multi-robot coordination, enabling the completion of complex tasks that would be intractable for individual robots. However, existing approaches to task allocation often assume that task requirements or reward functions are known and explicitly specified by …
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Multi task learning and incorporating common sense knowledge for question answering
… has been made in the recent years for this task, since the advent of deep learning and use of sequence to sequence models for NLP. This thesis deals with two complex tasks in Question Answering with their own inherent challenges: Multi Task Learning for Narrative Question Answering, which …
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Deep Structured Multi-Task Learning for Computer Vision in Autonomous Driving
… tool for solving almost any computer vision task, so state-of-the-art systems have been built by using the predictive capabilities of Convolutional Neural Networks (CNNs). Many of those systems use simple encoder–decoder based design, where an off-the-shelf CNN architecture is combined with a …
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Predicting Individual Components of the SOFA Score using Multi-Task Learning
… individual components of the SOFA score. We use multi-task learning frameworks to predict future values for the SOFA score components, with the goal of sharing information across the different tasks to improve overall predictive performance. We use approximately 53,000 days of time-series …
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Multi-Task Reinforcement Learning: From Single-Agent to Multi-Agent Systems
… of the technology. The ability to develop these multi-task, multi-agent drone systems is limited by the lack of available training environments, as well as deficiencies of multi-task learning due to a phenomenon known as catastrophic forgetting. In this thesis, we present a set of simulation …
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Optimal Task Scheduling and Flight Planning for Multi-Task Unmanned Aerial Vehicles
… components, the UAV is capable of conducting multiple tasks simultaneously. Coordinating different tasks to a multi-task UAV can be challenging. The reason is that tasks may require different levels of commitment and tolerate different latencies. Another reason is that multi-tasking can give …
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Video Scene Understanding: Semantic-based representation, Temporal Variation Modeling, Multi-Task Learning
… descriptors in videos, and (iii) proposing a multitask learning framework to leverage the huge amount of unlabeled videos. The first category covers a method for enriching visual words that contain local motion information but they lack information about the cause of the motion. Our proposed …
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Variational Multi-Task Models for Image Analysis: Applications to Magnetic Resonance Imaging
… the study and development of several variational multi-task models for solving inverse problems in imaging, with a particular focus on Magnetic Resonance Imaging (MRI). In most image processing problems, one usually deals with the reconstruction task, i.e., the task of reconstructing an image from …
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Predicting Performance Run-time Metrics in Fog Manufacturing using Multi-task Learning
… services based on the optimal computation task offloading, scheduling, and hardware autoscaling strategies to finish the computation tasks on time without compromising on the quality of the computation service. A prerequisite for adapting such optimal strategies is to accurately predict the …
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A Novel Approach to Movement Profiling: Multi-Task Classification for Enhanced Orthopedics Assessment
… from participants during a series of functional tasks, chosen for their clinical relevance in assessing lower-limb biomechanics. Preprocessing steps, including noise filtering, temporal resampling, and gap-filling, were applied to the raw data to ensure consistency and comparability across …
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