Browsing by Title
Now showing items 74744-74763 of 142666
-
Machine Learning for Databases
(ACM|The First International Conference on AI-ML-Systems, 2021-10-21) -
Machine learning for deep elastic strain engineering of semiconductor electronic band structure and effective mass
(Springer Science and Business Media LLC, 2021)<jats:title>Abstract</jats:title><jats:p>The controlled introduction of elastic strains is an appealing strategy for modulating the physical properties of semiconductor materials. With the recent discovery of large elastic ... -
Machine learning for detection of cyberattacks on industrial control systems
(Massachusetts Institute of Technology, 2023-02)Senior executives for industrial systems are increasingly facing the need to reassess their cyber risk as cyberattacks are on a steep rise. This is because of the rapid digitalization of traditional industries, designed ... -
Machine learning for detection of fake news
(Massachusetts Institute of Technology, 2018)Recent political events have lead to an increase in the popularity and spread of fake news. As demonstrated by the widespread effects of the large onset of fake news, humans are inconsistent if not outright poor detectors ... -
Machine Learning for Downstream Oil & Gas Refineries: Applications for Solvent Deasphalting
(Massachusetts Institute of Technology, 2021-09)This thesis seeks to provide continuous DAO yield estimations for an SDA unit by constructing modern machine learning models using data sets from a commercial downstream oil and gas refinery in the United States. These ... -
Machine Learning for Efficient Sampling-Based Algorithms in Robust Multi-Agent Planning Under Uncertainty
(American Institute of Aeronautics and Astronautics (AIAA), 2017-01)Robust multi-agent planning algorithms have been developed to assign tasks to cooperative teams of robots operating under various uncertainties. Often, it is difficult to evaluate the robustness of potential task assignments ... -
Machine Learning for High-Energy Collider Physics
(Massachusetts Institute of Technology, 2021-06)Fundamental physics, in particular high-energy collider physics, seeks to understand the natural world at the smallest scales, leading experimentally to the creation of large, complex datasets. Machine learning comprises ... -
Machine Learning for Human Design: Developing Next Generation Sketch-Based Tools
(Massachusetts Institute of Technology, 2021-06)Formal computational approaches in the realm of engineering and architecture, such as parametric modelling and optimization, are becoming increasingly powerful, allowing for systematic and rigorous design processes. However, ... -
Machine learning for medical ultrasound: status, methods, and future opportunities
(Springer US, 2018-02-28)Abstract Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image ... -
Machine Learning for Modeling and Control of a Packaging Manufacturing Process
(Massachusetts Institute of Technology, 2023-09)Process control is a key component of industrial automation. Irrespective of the specific product being manufactured, there is always a need for a controller to decide on specific inputs to the system such that the process ... -
Machine Learning for Novel Thermal-Materials Discovery: Early Successes, Opportunities, and Challenges
(Engineered Science Publisher, 2018-12)High-throughput computational and experimental design of materials aided by machine learning have become an increasingly important field in material science. This area of research has emerged in leaps and bounds in the ... -
Machine learning for nuclear fission systems : preliminary investigation of an autonomous control system for the MGEP
(Massachusetts Institute of Technology, 2019)Commercial nuclear technology today is facing challenges due to both economic viability and concerns over safety. Next-generation reactors could potentially improve with respect to both concerns through recent advancements ... -
Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis
(Nature Publishing Group, 2017-12)Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of ... -
Machine Learning for Out of Distribution Database Workloads
(Massachusetts Institute of Technology, 2024-02)DBMS query optimizers are designed using several heuristics to make decisions, such as simplifying assumptions in cardinality estimation, or cost model assumptions for predicting query latencies. With the rise of cloud ... -
Machine learning for pain assessment and management
(Massachusetts Institute of Technology, 2020)Pain is a subjective distressing experience associated with actual or potential tissue damage with sensory, emotional, cognitive and social components. This work aims to develop automatic methods for quantifying pain ... -
Machine learning for patient-adaptive ectopic beat classification
(Massachusetts Institute of Technology, 2010)Physicians require automated techniques to accurately analyze the vast amount of physiological data collected by continuous monitoring devices. In this thesis, we consider one analysis task in particular, the classification ... -
Machine Learning for Phonon Thermal Transport
(Massachusetts Institute of Technology, 2022-09)Efficient generation, transport, conversion, and storage of energy are essential to support our modern society and combat global climate change. As one of the major energy carriers, phonons play an indispensable role in ... -
Machine learning for problems with missing and uncertain data with applications to personalized medicine
(Massachusetts Institute of Technology, 2019)When we try to apply statistical learning in real-world applications, we frequently encounter data which include missing and uncertain values. This thesis explores the problem of learning from missing and uncertain data ... -
Machine Learning for Pulmonary and Critical Care Medicine: A Narrative Review
(Springer Healthcare, 2020-02-05)Abstract Machine learning (ML) is a discipline of computer science in which statistical methods are applied to data in order to classify, predict, or optimize, based on previously observed data. Pulmonary ... -
Machine Learning for Pulmonary and Critical Care Medicine: A Narrative Review
(Springer Healthcare, 2020-02-05)Abstract Machine learning (ML) is a discipline of computer science in which statistical methods are applied to data in order to classify, predict, or optimize, based on previously observed data. Pulmonary and critical ...
