SearchSkip to Search Results
- 97Machine Learning
- 17Artificial Intelligence
- 13Reinforcement Learning
- 8Computer Vision
- 6Deep Learning
- 86Graduate Studies and Research, Faculty of
- 86Graduate Studies and Research, Faculty of/Theses and Dissertations
- 8Computing Science, Department of
- 7Computing Science, Department of/Technical Reports (Computing Science)
- 1Chemical and Materials Engineering, Department of
- 1Chemical and Materials Engineering, Department of/Process Systems Engineering
- 49Department of Computing Science
- 13Department of Electrical and Computer Engineering
- 11Department of Civil and Environmental Engineering
- 5Department of Chemical and Materials Engineering
- 3Department of Mechanical Engineering
- 1Department of Biomedical Engineering
Considering the high rates of labor resources in construction projects clearly indicates the importance of appropriate labor resource management methods. Accurate labor resource allocation is a substantial step towards successful labor resource management. With the recent developments in the area...
The ubiquity of the Internet-of-Things (IoT) devices in everyday life allows various sensors to be utilized in networked systems for solving a number of real-world problems. Models utilizing specific sensing modalities achieve impressive performance in understanding human activity and are used in...
The management of project documentation involves processing a large amount of important information embedded in different contract and project specification documents. Although contract-related documentation is critical for effective information flow and—in turn—successful project management, it...
A Hierarchical Constrained Reinforcement Learning for Optimization of Bitumen Recovery Rate in a Primary Separation VesselDownload
This work proposes a two-level hierarchical constrained control structure for reinforcement learning (RL) with application in a Primary Separation Vessel (PSV). The lower level is concerned with servo tracking and regulation of the interface level against variances in ore quality by manipulating...
The municipal drainage system is a key component of every modern city’s infrastructure. However, as the drainage system ages, its pipes gradually deteriorate at rates that vary based on the conditions of utilization (i.e., intrinsic conditions) and other extrinsic factors such as the presence of...
Data augmentation is a strong tool for enhancing the performance of deep learning models using different techniques to increase both the quantity and diversity of training data. Cutout was previously proposed, in the context of image classification, as a simple regularization technique that...
Learning about many things can provide numerous benefits to a reinforcement learning system. For example, learning many auxiliary value functions, in addition to optimizing the environmental reward, appears to improve both exploration and representation learning. The question we tackle in this...
Monte Carlo methods are a simple, effective, and widely deployed way of approximating integrals that prove too challenging for deterministic approaches. This thesis presents a number of contributions to the field of adaptive Monte Carlo methods. That is, approaches that automatically adjust the...
Research in unsupervised text generation has been gaining attention over the years. One recent approach is local search towards a heuristically defined objective, which specifies language fluency, semantic meanings, and other task-specific attributes. Search in the sentence space is realized by...
The predictive representations hypothesis is that representing the state of the world in terms of predictions about the future will result in good generalization. In this thesis, good generalization is specifically quantified by good learning performance in both accuracy and speed when predicting...