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Neural network gradient-based learning of black-box function interfaces
We propose a method for end-to-end training of a base neural network that integrates calls to existing black-box functions.
Rank and Rate: Multi-task Learning for Recommender Systems
The two main tasks in the Recommender Systems domain are the ranking and rating prediction tasks.
Estimate and Replace: A Novel Approach to Integrating Deep Neural Networks with Existing Applications
At inference time, we replace each estimator with its existing application counterpart and let the base network solve the task by interacting with the existing application.
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