1. Encoding architecture algebra
- Author
-
Bersier, Stephane and Chen-Lin, Xinyi
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Programming Languages ,Computer Science - Software Engineering - Abstract
Despite the wide variety of input types in machine learning, this diversity is often not fully reflected in their representations or model architectures, leading to inefficiencies throughout a model's lifecycle. This paper introduces an algebraic approach to constructing input-encoding architectures that properly account for the data's structure, providing a step toward achieving more typeful machine learning., Comment: 25 pages, 6 figures. Keywords: typeful, algebraic data types, tensors, structured data
- Published
- 2024