Multi-task learning method using gradient descent with applications, A
There is a critical need to develop classification methods that can robustly and accurately classify different objects in varying environments. Each environment in a classification problem can contain its own unique challenges which prevent traditional classifiers from performing well. To solve classification problems in different environments, multi-task learning (MTL) models have been applied that define each environment as a separate task. We discuss two existing MTL algorithms and explain how they are inefficient for situations involving high-dimensional data. A gradient descent-based MTL ...
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