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.
Results
Showing 1 to 20 of 4411 for “"ML"”.
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ML-driven clinical documentation
… by using novel machine learning methods to streamline the processes by which clinicians enter in new information and surface relevant details from past medical records. Our intelligent interface aids physicians as they type, allowing for automatic suggestion and live-tagging of clinical concepts …
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ML-assisted therapeutics for neurodegenerative disorders
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-12-04 without embargo terms
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How Data Drives ML Models Performance
… more important role in the machine learning (ML) pipeline. This thesis deepens the understanding of the effect of the data on model performance and reliability. First, we study how choice of training data affects model performance. We consider a transfer learning setting and present a …
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Harnessing AI/ML for advancing synthetic biology
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01
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Efficient ML Inference via Matrix-Vector Approximations
Efficient inference is a growing priority in deep learning, where large model sizes and increasing deployment demands pose challenges for latency, memory, and energy usage. This thesis presents a unified framework for evaluating approximation methods that accelerate inference by modifying weight …
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Implementing concurrency for an ML-based operating system
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and, Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
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Towards ML Models That We Can Deploy Confidently
As machine learning (ML) systems are deployed in the real world, the reliability and trustworthiness of these systems become an even more salient challenge. This thesis aims to address this challenge through two key thrusts: (1) making ML models more trustworthy by leveraging what has been …
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Improve and certify ML robustness by integrating exogenous information
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-08-01
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Democratizing data science through interactive curation of ML pipelines
… de-facto inhibiting a wider adoption of ML techniques in other fields. Existing libraries that claim to solve this problem, still require well-trained practitioners. Those frameworks involve heavy data preparation steps and are often too slow for interactive feedback from the user, …
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ML for Loop Gain Identification of DC/DC Converters
Control loop identification is necessary for evaluating the stability of switched power supplies and is therefore an important step during design and verification. Analytical models of power supplies often yield inaccurate predictions of the loop gain; therefore, power engineers traditionally must …
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Using FoxNet for TCP/IP networking in ML/OS
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
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DATA GOVERNANCE FRAMEWORK FOR ML-BASED, DATA-INTENSIVE DISTRIBUTED SYSTEMS
… analytics capabilities. Machine Learning (ML) and Internet of Things (IoT) technologies are increasingly integrated into these systems, enabling advanced data processing pipelines that span multiple organizational boundaries. Modern distributed data processing systems support critical …
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Counterfactual Prescriptions Via Hierarchical ML For Missed Chemotherapy Appointment Prevention
Missed medical appointments, including cancellations and no-shows, disrupt clinical workflows, reduce efficiency, and compromise patient care. Using 1.8 million chemotherapy appointments from the Dana-Farber Cancer Institute, this study develops a hierarchical machine learning framework that first …
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Ml Controllers With Memory For Robust Quadrotor Control And Research
… will explore different control architectures and ML control methods for a quadrotor, and in doing so develop a framework for testing and evaluation of non-classical controllers for future SimToReal research. The system we will control a Crazyflie 2.X quadrotor drone, and its pose will be measured …
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Differential DSP: An audio toolbox for end-to-end ml
The short-time Fourier transform (STFT) has been a staple of signal processing, often being the first step for many audio tasks. A very familiar process when using the STFT is the search for the best STFT parameters, as they often have significant side effects if chosen poorly. These parameters are …
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Improving project timelines using Al / ML to detect forecasting errors
This project focuses on the creation of a novel tool to detect and flag potential errors within Amgen's capacity management forecast data, in an automated manner using statistical analysis, artificial intelligence and machine learning. User interaction allows the tool to learn from experience, …
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Enabling Efficient ML Inference in SigmaOS with Model-Aware Scheduling
… and scheduling inefficiencies of multi-tenant ML serving by integrating the RayServe distributed model-serving framework into σOS, a cloud operating system that unifies container and serverless paradigms. The thesis also proposes two model-aware schedulers within σOS that intelligently routes …
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AI-ML Powered Pig Behavior Classification and Body Weight Prediction
Precision livestock farming technologies have been widely researched over the last decade. These technologies help in monitoring animal health and welfare parameters in a continuous, automated fashion. Under this umbrella of precision livestock farming, this study focuses on activity classification …
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Enabling CBRS experimentation and ML-based Incumbent Detection using OpenSAS
… the presence of users in the CBRS band. An ML-based feedforward neural net- work model is employed and trained using simulated radar waveforms as incumbent signals and captured 5G New Radio (NR) signals as a non-incumbent signal to predict whether the detected user is a radar incumbent or an …
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An evaluation of ML/I (EPS) macros for structured FORTRAN extensions
Typescript, etc.
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