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A survey and taxonomy of loss functions in machine learning
This survey aims to provide a reference of the most essential loss functions for both beginner and advanced machine learning practitioners.
Maximum entropy exploration in contextual bandits with neural networks and energy based models
This provides practitioners with new techniques that perform well in static and dynamic settings, and are particularly well suited to non-linear scenarios with continuous action spaces.
Composition and Style Attributes Guided Image Aesthetic Assessment
In this paper we propose a method for the automatic prediction of the aesthetics of an image that is based on the analysis of the semantic content, the artistic style and the composition of the image.
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