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http://arks.princeton.edu/ark:/88435/dsp013r074x89z| Title: | ORIGINAL ORIGINAL Brain-Based Machine Learning Algorithms |
| Authors: | Gaura, Alexander |
| Advisors: | Berry, Michael |
| Department: | Mathematics |
| Certificate Program: | Center for Statistics and Machine Learning |
| Class Year: | 2020 |
| Abstract: | Traditional neural network models are based on ideas from neuroscience that have since become outdated. This paper investigates the performance of new neural network models that are based on modern neuroscience and compares their performance to other models on similar datasets. In particular, these models are useful for unsupervised learning, and differ most in how they receive input, their layering, and their learning rule which is based on Hebbian plasticity. |
| URI: | http://arks.princeton.edu/ark:/88435/dsp013r074x89z |
| Type of Material: | Princeton University Senior Theses |
| Language: | en |
| Appears in Collections: | Mathematics, 1934-2020 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| GAURA-ALEXANDER-THESIS.pdf | 408.57 kB | Adobe PDF | Request a copy |
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