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- 9Chemometrics
- 5Gas Chromatography
- 4Interdisciplinarity
- 4Mass-spectrometry
- 3Machine Learning
- 4Szostak, R.
- 2Harynuk, James
- 1Adutwum, Lawrence A
- 1Adutwum, Lawrence A.
- 1Adutwum, Lawrence A.
- 1Alireza Kheradmand
- 37Graduate and Postdoctoral Studies (GPS), Faculty of
- 37Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 4Economics, Department of
- 3Biological Sciences, Department of
- 3Biological Sciences, Department of/Journal Articles (Biological Sciences)
- 3Economics, Department of/Journal Articles (Economics)
- 37Thesis
- 11Article (Published)
- 2Report
- 1Chapter
- 1Conference/Workshop Poster
- 1Conference/Workshop Presentation
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Toward Practical Reinforcement Learning Algorithms: Classification Based Policy Iteration and Model-Based Learning
DownloadSpring 2017
In this dissertation, we advance the theoretical understanding of two families of Reinforcement Learning (RL) methods: Classification-based policy iteration (CBPI) and model-based reinforcement learning (MBRL) with factored semi-linear models. In contrast to generalized policy iteration, CBPI...
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Understanding the Chemistry of Conversion of Model Compounds and Biomass by Hydrous Pyrolysis Based on Spectroscopic Data Using Data Fusion, Data Mining, and Chemometrics
DownloadFall 2019
Encoding the presence of multispecies in a complex system, difficulty in characterizing the physical constituents of the products with analytical instruments along with developing the causality or modeling between these groups are some major challenges in a complex system such as biomass...
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Unique Ion Filter: A data reduction tool for GC/MS data preprocessing prior to chemometric analysis
Download2014
Harynuk, James, Adutwum, Lawrence A.
Using raw GC/MS data as the X-block for chemometric modeling has the potential to provide better classification models for complex samples when compared to using the total ion current (TIC), extracted ion chromatograms/profiles (EIC/EIP), or integrated peak tables. However, the abundance of raw...
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Fall 2021
Deep neural network (DNN) has been developed rapidly in years. While it shows promising results in various tasks of computer vision, DNN typically suffers from accuracy loss due to the domain shift from a source domain to a target domain. To mitigate the accuracy loss without the label from...
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Fall 2011
In this thesis, we focus on topics relevant to developing and deploying large-scale wireless sensor network (WSN) applications within real dynamic urban environments. Given few reported experiences in the literature, we designed our own such network to provide a foundation for our research. The...