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- Description:
- In this document, I demonstrate that: 1) Linear basis functions cannot outperform nonlinear ones to represent hand kinematics 2) Nonlinear autoencoders outperform PCA on the dimensionality reduction of hand kinematics, 3) Nonlinear autoencoders outperform PCA in human gait representation and recurrent nonlinear autoencoders can seamlessly express the temporal dynamics, 4)...
- Keyword:
- kinematics, prosthetics, machine learning, gait, dimensionality reduction, and hand
- Subject:
- Engineering
- Creator:
- Portnova-Fahreeva, Alexandra
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 09/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:16176 and etdadmin_upload_920776
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- Description:
- Mixing by cutting-and-shuffling (like that for a deck of cards or a Rubik's cube) is a paradigm that has not been studied in detail even though it can be applied in a variety of situations including the mixing of granular materials. Mathematically, cutting- and-shuffling is described by piecewise isometries (PWIs),...
- Keyword:
- granular materials, mixing, machine learning, piecewise isometries, cutting-and-shuffling, and interval exchange transforms
- Subject:
- Applied mathematics, Chemical engineering, and Mechanical engineering
- Creator:
- Lynn, Thomas Ferguson
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 06/22/2022
- Date Created:
- 2022-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_881325 and http://dissertations.umi.com/northwestern:15951
-
- Description:
- The task of classification has been increasingly attracting attention from researchers in recent years. The objective is to assign labels given attributes of samples. The classification task is practical in real-world applications and is widely explored in fields such as computer vision, natural language processing and information retrieval. The recent...
- Keyword:
- neural networks, classification, machine learning, and deep learning
- Subject:
- Artificial intelligence
- Creator:
- Xu, Yiming
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- http://dissertations.umi.com/northwestern:15370 and etdadmin_upload_778963
-
- Description:
- This dissertation asks how researchers can create more equitable algorithmic systems. Ultimately, this thesis explores methods and implications of representing subjects of analysis in the design and evaluation of algorithmic systems. I also unpack how algorithmic tools measure and quantify human behavior, giving heed to the potential impacts of these...
- Keyword:
- algorithms, machine learning, human-computer interaction, social discrimination, age discrimination, and algorithmic fairness
- Subject:
- Information science, Social research, and Computer science
- Creator:
- Díaz, Mark
- Owner:
- Scholarly Digital Publishing
- Language:
- en
- Date Uploaded:
- 02/01/2021
- Date Created:
- 2020-01-01
- Resource Type:
- Dissertation
- Alternate Identifier:
- etdadmin_upload_762101 and http://dissertations.umi.com/northwestern:15226
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- Description:
- The ability of a machine to synthesize textual output in a form of human language is a long-standing goal in a field of artificial intelligence and has wide-range of applications such as spell correction, speech recognition, machine translation, abstractive summarization, etc. The statistical approach to enable such ability mainly involves...
- Keyword:
- language generation, machine learning, natural language processing, deep learning, dictionary definitions, and language modeling
- Subject:
- Electrical and Computer Engineering
- Creator:
- Thanapon Noraset
- Owner:
- Scholarly Digital Publishing
- Date Uploaded:
- 04/01/2019
- Date Modified:
- 04/01/2019
- Date Created:
- 2018-01-01
- Resource Type:
- Dissertation